{"id":26068,"date":"2025-03-25T14:11:47","date_gmt":"2025-03-25T07:11:47","guid":{"rendered":"https:\/\/interdata.vn\/blog\/?p=26068"},"modified":"2025-03-25T14:20:19","modified_gmt":"2025-03-25T07:20:19","slug":"convolutional-neural-network-la-gi","status":"publish","type":"post","link":"https:\/\/interdata.vn\/blog\/convolutional-neural-network-la-gi\/","title":{"rendered":"Convolutional Neural Network l\u00e0 g\u00ec? A-Z v\u1ec1 thu\u1eadt to\u00e1n CNN"},"content":{"rendered":"<div id=\"ez-toc-container\" class=\"ez-toc-v2_0_84 counter-hierarchy ez-toc-counter ez-toc-white ez-toc-container-direction\">\n<div class=\"ez-toc-title-container\">\n<p class=\"ez-toc-title\" style=\"cursor:inherit\">N\u1ed8I DUNG<\/p>\n<span class=\"ez-toc-title-toggle\"><a href=\"#\" class=\"ez-toc-pull-right ez-toc-btn ez-toc-btn-xs ez-toc-btn-default ez-toc-toggle\" aria-label=\"Toggle Table of Content\"><span class=\"ez-toc-js-icon-con\"><span class=\"\"><span class=\"eztoc-hide\" style=\"display:none;\">Toggle<\/span><span class=\"ez-toc-icon-toggle-span\"><svg style=\"fill: #999;color:#999\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" class=\"list-377408\" width=\"20px\" height=\"20px\" viewBox=\"0 0 24 24\" fill=\"none\"><path d=\"M6 6H4v2h2V6zm14 0H8v2h12V6zM4 11h2v2H4v-2zm16 0H8v2h12v-2zM4 16h2v2H4v-2zm16 0H8v2h12v-2z\" fill=\"currentColor\"><\/path><\/svg><svg style=\"fill: #999;color:#999\" class=\"arrow-unsorted-368013\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" width=\"10px\" height=\"10px\" viewBox=\"0 0 24 24\" version=\"1.2\" baseProfile=\"tiny\"><path d=\"M18.2 9.3l-6.2-6.3-6.2 6.3c-.2.2-.3.4-.3.7s.1.5.3.7c.2.2.4.3.7.3h11c.3 0 .5-.1.7-.3.2-.2.3-.5.3-.7s-.1-.5-.3-.7zM5.8 14.7l6.2 6.3 6.2-6.3c.2-.2.3-.5.3-.7s-.1-.5-.3-.7c-.2-.2-.4-.3-.7-.3h-11c-.3 0-.5.1-.7.3-.2.2-.3.5-.3.7s.1.5.3.7z\"\/><\/svg><\/span><\/span><\/span><\/a><\/span><\/div>\n<nav><ul class='ez-toc-list ez-toc-list-level-1 eztoc-toggle-hide-by-default' ><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-1\" href=\"https:\/\/interdata.vn\/blog\/convolutional-neural-network-la-gi\/#Convolutional-Neural-Network-la-gi\" >Convolutional Neural Network l\u00e0 g\u00ec?<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-2\" href=\"https:\/\/interdata.vn\/blog\/convolutional-neural-network-la-gi\/#Cac-lop-co-ban-cua-mang-Convolutional-Neural-Network\" >C\u00e1c l\u1edbp c\u01a1 b\u1ea3n c\u1ee7a m\u1ea1ng Convolutional Neural Network<\/a><ul class='ez-toc-list-level-3' ><li class='ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-3\" href=\"https:\/\/interdata.vn\/blog\/convolutional-neural-network-la-gi\/#Lop-tich-chap-Convolutional-Layer\" >L\u1edbp t\u00edch ch\u1eadp (Convolutional Layer)<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-4\" href=\"https:\/\/interdata.vn\/blog\/convolutional-neural-network-la-gi\/#Lop-ReLU-ReLU-Layer\" >L\u1edbp ReLU (ReLU Layer)<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-5\" href=\"https:\/\/interdata.vn\/blog\/convolutional-neural-network-la-gi\/#Lop-gop-Pooling-Layer\" >L\u1edbp g\u1ed9p (Pooling Layer)<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-6\" href=\"https:\/\/interdata.vn\/blog\/convolutional-neural-network-la-gi\/#Lop-ket-noi-day-du-Fully-Connected-Layer\" >L\u1edbp k\u1ebft n\u1ed1i \u0111\u1ea7y \u0111\u1ee7 (Fully Connected Layer)<\/a><\/li><\/ul><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-7\" href=\"https:\/\/interdata.vn\/blog\/convolutional-neural-network-la-gi\/#Thuat-toan-CNN-co-cau-truc-nhu-the-nao\" >Thu\u1eadt to\u00e1n CNN c\u00f3 c\u1ea5u tr\u00fac nh\u01b0 th\u1ebf n\u00e0o?<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-8\" href=\"https:\/\/interdata.vn\/blog\/convolutional-neural-network-la-gi\/#Uu-nhuoc-diem-cua-Convolutional-Neural-Network\" >\u01afu, nh\u01b0\u1ee3c \u0111i\u1ec3m c\u1ee7a Convolutional Neural Network<\/a><ul class='ez-toc-list-level-3' ><li class='ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-9\" href=\"https:\/\/interdata.vn\/blog\/convolutional-neural-network-la-gi\/#Uu-diem-cua-CNN-la-gi\" >\u01afu \u0111i\u1ec3m c\u1ee7a CNN l\u00e0 g\u00ec?<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-10\" href=\"https:\/\/interdata.vn\/blog\/convolutional-neural-network-la-gi\/#Nhuoc-diem-cua-CNN-la-gi\" >Nh\u01b0\u1ee3c \u0111i\u1ec3m c\u1ee7a CNN l\u00e0 g\u00ec?<\/a><\/li><\/ul><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-11\" href=\"https:\/\/interdata.vn\/blog\/convolutional-neural-network-la-gi\/#Su-khac-biet-giua-CNN-so-voi-mang-no-ron-truyen-thong\" >S\u1ef1 kh\u00e1c bi\u1ec7t gi\u1eefa CNN so v\u1edbi m\u1ea1ng n\u01a1-ron truy\u1ec1n th\u1ed1ng<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-12\" href=\"https:\/\/interdata.vn\/blog\/convolutional-neural-network-la-gi\/#Ung-dung-cua-Convolutional-Neural-Network\" >\u1ee8ng d\u1ee5ng c\u1ee7a Convolutional Neural Network<\/a><ul class='ez-toc-list-level-3' ><li class='ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-13\" href=\"https:\/\/interdata.vn\/blog\/convolutional-neural-network-la-gi\/#1-Y-te\" >1. Y t\u1ebf<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-14\" href=\"https:\/\/interdata.vn\/blog\/convolutional-neural-network-la-gi\/#2-O-to\" >2. \u00d4 t\u00f4<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-15\" href=\"https:\/\/interdata.vn\/blog\/convolutional-neural-network-la-gi\/#3-Mang-xa-hoi\" >3. M\u1ea1ng x\u00e3 h\u1ed9i<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-16\" href=\"https:\/\/interdata.vn\/blog\/convolutional-neural-network-la-gi\/#4-Thuong-mai-dien-tu\" >4. Th\u01b0\u01a1ng m\u1ea1i \u0111i\u1ec7n t\u1eed<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-17\" href=\"https:\/\/interdata.vn\/blog\/convolutional-neural-network-la-gi\/#5-Tro-ly-ao\" >5. Tr\u1ee3 l\u00fd \u1ea3o<\/a><\/li><\/ul><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-18\" href=\"https:\/\/interdata.vn\/blog\/convolutional-neural-network-la-gi\/#Cach-chon-tham-so-cho-Convolutional-Neural-Network-CNN\" >C\u00e1ch ch\u1ecdn tham s\u1ed1 cho Convolutional Neural Network (CNN)<\/a><\/li><\/ul><\/nav><\/div>\n<p>Trong l\u0129nh v\u1ef1c <a href=\"https:\/\/interdata.vn\/blog\/tri-tue-nhan-tao-ai\/\">tr\u00ed tu\u1ec7 nh\u00e2n t\u1ea1o<\/a> (AI), Convolutional Neural Network (CNN) l\u00e0 m\u1ed9t thu\u1eadt to\u00e1n h\u1ecdc s\u00e2u (Deep Learning) \u0111\u1eb7c bi\u1ec7t hi\u1ec7u qu\u1ea3 trong x\u1eed l\u00fd h\u00ecnh \u1ea3nh v\u00e0 nh\u1eadn di\u1ec7n \u0111\u1ed1i t\u01b0\u1ee3ng. CNN c\u00f3 kh\u1ea3 n\u0103ng t\u1ef1 \u0111\u1ed9ng h\u1ecdc c\u00e1c \u0111\u1eb7c tr\u01b0ng t\u1eeb d\u1eef li\u1ec7u, gi\u00fap c\u1ea3i thi\u1ec7n \u0111\u1ed9 ch\u00ednh x\u00e1c v\u00e0 t\u1ed1i \u01b0u h\u00f3a hi\u1ec7u su\u1ea5t. B\u00e0i vi\u1ebft n\u00e0y s\u1ebd gi\u00fap b\u1ea1n hi\u1ec3u r\u00f5 v\u1ec1 c\u1ea5u tr\u00fac <a href=\"https:\/\/interdata.vn\/blog\/convolutional-neural-network-la-gi\/\"><strong>m\u1ea1ng Convolutional Neural Network l\u00e0 g\u00ec<\/strong><\/a>, c\u00e1c l\u1edbp c\u01a1 b\u1ea3n, \u01b0u nh\u01b0\u1ee3c \u0111i\u1ec3m, c\u0169ng nh\u01b0 \u1ee9ng d\u1ee5ng th\u1ef1c t\u1ebf c\u1ee7a m\u00f4 h\u00ecnh n\u00e0y trong nhi\u1ec1u l\u0129nh v\u1ef1c.<\/p>\n<h2><span class=\"ez-toc-section\" id=\"Convolutional-Neural-Network-la-gi\"><\/span>Convolutional Neural Network l\u00e0 g\u00ec?<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p><strong>M\u1ea1ng N\u01a1-ron T\u00edch Ch\u1eadp, hay Convolutional Neural Network (CNN)<\/strong>, l\u00e0 m\u1ed9t lo\u1ea1i m\u00f4 h\u00ecnh h\u1ecdc s\u00e2u (deep learning) c\u1ef1c k\u1ef3 hi\u1ec7u qu\u1ea3 trong l\u0129nh v\u1ef1c tr\u00ed tu\u1ec7 nh\u00e2n t\u1ea1o (AI), \u0111\u1eb7c bi\u1ec7t n\u1ed5i tr\u1ed9i trong c\u00e1c t\u00e1c v\u1ee5 li\u00ean quan \u0111\u1ebfn x\u1eed l\u00fd \u1ea3nh. CNN l\u00e0 n\u1ec1n t\u1ea3ng \u0111\u1ec3 x\u00e2y d\u1ef1ng c\u00e1c h\u1ec7 th\u1ed1ng th\u00f4ng minh v\u1edbi \u0111\u1ed9 ch\u00ednh x\u00e1c v\u01b0\u1ee3t tr\u1ed9i, nh\u1edd kh\u1ea3 n\u0103ng t\u1ef1 \u0111\u1ed9ng h\u1ecdc v\u00e0 tr\u00edch xu\u1ea5t c\u00e1c \u0111\u1eb7c \u0111i\u1ec3m quan tr\u1ecdng t\u1eeb d\u1eef li\u1ec7u h\u00ecnh \u1ea3nh.<\/p>\n<p>CNN x\u1eed l\u00fd d\u1eef li\u1ec7u \u1ea3nh b\u1eb1ng c\u00e1ch <strong>s\u1eed d\u1ee5ng m\u1ed9t lo\u1ea1t c\u00e1c ph\u00e9p to\u00e1n t\u00edch ch\u1eadp<\/strong> (convolution). \u0110i\u1ec1u n\u00e0y gi\u00fap m\u00f4 h\u00ecnh nh\u1eadn di\u1ec7n c\u00e1c \u0111\u1eb7c tr\u01b0ng (features) quan tr\u1ecdng trong \u1ea3nh m\u1ed9t c\u00e1ch hi\u1ec7u qu\u1ea3.<\/p>\n<figure id=\"attachment_26076\" aria-describedby=\"caption-attachment-26076\" style=\"width: 800px\" class=\"wp-caption aligncenter\"><img loading=\"lazy\" decoding=\"async\" src=\"https:\/\/interdata.vn\/blog\/wp-content\/uploads\/2025\/03\/Convolutional-Neural-Network-la-gi.png\" alt=\"Convolutional Neural Network l\u00e0 g\u00ec?\" width=\"800\" height=\"500\" class=\"size-full wp-image-26076\" title=\"\" srcset=\"https:\/\/interdata.vn\/blog\/wp-content\/uploads\/2025\/03\/Convolutional-Neural-Network-la-gi.png 800w, https:\/\/interdata.vn\/blog\/wp-content\/uploads\/2025\/03\/Convolutional-Neural-Network-la-gi-300x188.png 300w, https:\/\/interdata.vn\/blog\/wp-content\/uploads\/2025\/03\/Convolutional-Neural-Network-la-gi-768x480.png 768w, https:\/\/interdata.vn\/blog\/wp-content\/uploads\/2025\/03\/Convolutional-Neural-Network-la-gi-750x469.png 750w\" sizes=\"auto, (max-width: 800px) 100vw, 800px\" \/><figcaption id=\"caption-attachment-26076\" class=\"wp-caption-text\">Convolutional Neural Network l\u00e0 g\u00ec?<\/figcaption><\/figure>\n<p>V\u00ed d\u1ee5 th\u1ef1c t\u1ebf, CNN \u0111\u01b0\u1ee3c \u1ee9ng d\u1ee5ng r\u1ed9ng r\u00e3i trong nh\u1eadn d\u1ea1ng khu\u00f4n m\u1eb7t, ph\u00e2n lo\u1ea1i \u0111\u1ed1i t\u01b0\u1ee3ng trong \u1ea3nh, v\u00e0 nhi\u1ec1u b\u00e0i to\u00e1n kh\u00e1c. C\u00e1c \u00f4ng l\u1edbn c\u00f4ng ngh\u1ec7 nh\u01b0 Facebook v\u00e0 Google \u0111\u00e3 v\u00e0 \u0111ang s\u1eed d\u1ee5ng CNN \u0111\u1ec3 n\u00e2ng cao kh\u1ea3 n\u0103ng nh\u1eadn di\u1ec7n h\u00ecnh \u1ea3nh tr\u00ean c\u00e1c n\u1ec1n t\u1ea3ng c\u1ee7a h\u1ecd.<\/p>\n<p>V\u1ec1 m\u1eb7t ho\u1ea1t \u0111\u1ed9ng, khi m\u1ed9t h\u00ecnh \u1ea3nh \u0111\u1ea7u v\u00e0o \u0111\u01b0\u1ee3c \u0111\u01b0a v\u00e0o m\u1ea1ng CNN, n\u00f3 s\u1ebd tr\u1ea3i qua m\u1ed9t chu\u1ed7i c\u00e1c b\u01b0\u1edbc x\u1eed l\u00fd. Ban \u0111\u1ea7u, h\u00ecnh \u1ea3nh \u0111\u01b0\u1ee3c x\u1eed l\u00fd qua c\u00e1c l\u1edbp t\u00edch ch\u1eadp (convolutional layers), s\u1eed d\u1ee5ng c\u00e1c b\u1ed9 l\u1ecdc (filters) \u0111\u1ec3 tr\u00edch xu\u1ea5t \u0111\u1eb7c tr\u01b0ng. Sau \u0111\u00f3, d\u1eef li\u1ec7u \u0111i qua c\u00e1c l\u1edbp k\u1ebft n\u1ed1i \u0111\u1ea7y \u0111\u1ee7 (fully connected layers) v\u00e0 cu\u1ed1i c\u00f9ng l\u00e0 l\u1edbp ph\u00e2n lo\u1ea1i (classification layer), th\u01b0\u1eddng s\u1eed d\u1ee5ng h\u00e0m Softmax.<\/p>\n<p>C\u00e1c l\u1edbp n\u00e0y t\u00ednh to\u00e1n x\u00e1c su\u1ea5t cho c\u00e1c l\u1edbp \u0111\u1ed1i t\u01b0\u1ee3ng kh\u00e1c nhau, v\u00e0 k\u1ebft qu\u1ea3 cu\u1ed1i c\u00f9ng cho bi\u1ebft kh\u1ea3 n\u0103ng \u0111\u1ed1i t\u01b0\u1ee3ng trong \u1ea3nh thu\u1ed9c v\u1ec1 l\u1edbp n\u00e0o.<\/p>\n<h2><span class=\"ez-toc-section\" id=\"Cac-lop-co-ban-cua-mang-Convolutional-Neural-Network\"><\/span>C\u00e1c l\u1edbp c\u01a1 b\u1ea3n c\u1ee7a m\u1ea1ng Convolutional Neural Network<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>M\u1ed9t m\u1ea1ng n\u01a1-ron t\u00edch ch\u1eadp (CNN) bao g\u1ed3m c\u00e1c l\u1edbp c\u01a1 b\u1ea3n sau:<\/p>\n<h3><span class=\"ez-toc-section\" id=\"Lop-tich-chap-Convolutional-Layer\"><\/span>L\u1edbp t\u00edch ch\u1eadp (Convolutional Layer)<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p>\u0110\u00e2y l\u00e0 <strong>l\u1edbp quan tr\u1ecdng nh\u1ea5t<\/strong> c\u1ee7a CNN, th\u1ef1c hi\u1ec7n ph\u1ea7n l\u1edbn c\u00e1c ph\u00e9p t\u00ednh to\u00e1n. C\u00e1c y\u1ebfu t\u1ed1 then ch\u1ed1t c\u1ee7a l\u1edbp n\u00e0y bao g\u1ed3m: <strong>stride<\/strong> (b\u01b0\u1edbc tr\u01b0\u1ee3t), <strong>padding<\/strong> (ph\u1ea7n \u0111\u1ec7m), <strong>filter map<\/strong> (b\u1ea3n \u0111\u1ed3 b\u1ed9 l\u1ecdc), v\u00e0 <strong>feature map<\/strong> (b\u1ea3n \u0111\u1ed3 \u0111\u1eb7c tr\u01b0ng).<\/p>\n<p>CNN ho\u1ea1t \u0111\u1ed9ng b\u1eb1ng c\u00e1ch t\u1ea1o ra c\u00e1c <strong>b\u1ed9 l\u1ecdc (filter)<\/strong> v\u00e0 \u00e1p d\u1ee5ng ch\u00fang l\u00ean t\u1eebng v\u00f9ng nh\u1ecf c\u1ee7a h\u00ecnh \u1ea3nh. C\u00e1c b\u1ed9 l\u1ecdc n\u00e0y, c\u00f2n g\u1ecdi l\u00e0 <strong>filter map<\/strong>, l\u00e0 c\u00e1c ma tr\u1eadn 3 chi\u1ec1u ch\u1ee9a c\u00e1c <a href=\"https:\/\/interdata.vn\/blog\/tham-so-parameter-la-gi\/\">tham s\u1ed1<\/a> (parameter) d\u01b0\u1edbi d\u1ea1ng c\u00e1c gi\u00e1 tr\u1ecb s\u1ed1.<\/p>\n<ul>\n<li><strong>Stride<\/strong> l\u00e0 kho\u1ea3ng c\u00e1ch (t\u00ednh b\u1eb1ng pixel) m\u00e0 b\u1ed9 l\u1ecdc di chuy\u1ec3n qua h\u00ecnh \u1ea3nh theo chi\u1ec1u ngang v\u00e0 chi\u1ec1u d\u1ecdc.<\/li>\n<li><strong>Padding<\/strong> l\u00e0 vi\u1ec7c th\u00eam c\u00e1c gi\u00e1 tr\u1ecb 0 (zero padding) xung quanh vi\u1ec1n c\u1ee7a \u1ea3nh \u0111\u1ea7u v\u00e0o. Vi\u1ec7c n\u00e0y gi\u00fap ki\u1ec3m so\u00e1t k\u00edch th\u01b0\u1edbc c\u1ee7a feature map \u0111\u1ea7u ra.<\/li>\n<li><strong>Feature map<\/strong> l\u00e0 k\u1ebft qu\u1ea3 c\u1ee7a ph\u00e9p to\u00e1n t\u00edch ch\u1eadp gi\u1eefa b\u1ed9 l\u1ecdc v\u00e0 m\u1ed9t v\u00f9ng c\u1ee7a h\u00ecnh \u1ea3nh. N\u00f3 th\u1ec3 hi\u1ec7n m\u1ee9c \u0111\u1ed9 &#8220;ph\u00f9 h\u1ee3p&#8221; gi\u1eefa b\u1ed9 l\u1ecdc v\u00e0 v\u00f9ng \u1ea3nh \u0111\u00f3.<\/li>\n<\/ul>\n<h3><span class=\"ez-toc-section\" id=\"Lop-ReLU-ReLU-Layer\"><\/span>L\u1edbp ReLU (ReLU Layer)<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p>C\u00f2n \u0111\u01b0\u1ee3c g\u1ecdi l\u00e0 <strong>h\u00e0m k\u00edch ho\u1ea1t (activation function)<\/strong>, ReLU (Rectified Linear Unit) l\u00e0 m\u1ed9t h\u00e0m phi tuy\u1ebfn \u0111\u01b0\u1ee3c \u00e1p d\u1ee5ng sau l\u1edbp t\u00edch ch\u1eadp. H\u00e0m ReLU c\u00f3 d\u1ea1ng: f(x) = max(0, x). N\u00f3 gi\u00fap m\u00f4 ph\u1ecfng ho\u1ea1t \u0111\u1ed9ng c\u1ee7a c\u00e1c n\u01a1-ron th\u1ea7n kinh, ch\u1ec9 cho ph\u00e9p c\u00e1c t\u00edn hi\u1ec7u d\u01b0\u01a1ng \u0111i qua.<\/p>\n<p>ReLU \u0111\u01b0\u1ee3c \u01b0a chu\u1ed9ng trong hu\u1ea5n luy\u1ec7n m\u1ea1ng n\u01a1-ron s\u00e2u v\u00ec <strong>t\u00ednh \u0111\u01a1n gi\u1ea3n v\u00e0 hi\u1ec7u qu\u1ea3<\/strong> trong vi\u1ec7c gi\u1ea3i quy\u1ebft v\u1ea5n \u0111\u1ec1 &#8220;vanishing gradient&#8221; (gradient bi\u1ebfn m\u1ea5t). C\u00e1c h\u00e0m k\u00edch ho\u1ea1t kh\u00e1c bao g\u1ed3m: Tanh, Sigmoid, Leaky ReLU, Maxout.<\/p>\n<figure id=\"attachment_26079\" aria-describedby=\"caption-attachment-26079\" style=\"width: 770px\" class=\"wp-caption aligncenter\"><img loading=\"lazy\" decoding=\"async\" src=\"https:\/\/interdata.vn\/blog\/wp-content\/uploads\/2025\/03\/Cac-lop-co-ban-cua-mang-Convolutional-Neural-Network.webp\" alt=\"C\u00e1c l\u1edbp c\u01a1 b\u1ea3n c\u1ee7a m\u1ea1ng Convolutional Neural Network\" width=\"770\" height=\"768\" class=\"size-full wp-image-26079\" title=\"\" srcset=\"https:\/\/interdata.vn\/blog\/wp-content\/uploads\/2025\/03\/Cac-lop-co-ban-cua-mang-Convolutional-Neural-Network.webp 770w, https:\/\/interdata.vn\/blog\/wp-content\/uploads\/2025\/03\/Cac-lop-co-ban-cua-mang-Convolutional-Neural-Network-300x300.webp 300w, https:\/\/interdata.vn\/blog\/wp-content\/uploads\/2025\/03\/Cac-lop-co-ban-cua-mang-Convolutional-Neural-Network-150x150.webp 150w, https:\/\/interdata.vn\/blog\/wp-content\/uploads\/2025\/03\/Cac-lop-co-ban-cua-mang-Convolutional-Neural-Network-768x766.webp 768w, https:\/\/interdata.vn\/blog\/wp-content\/uploads\/2025\/03\/Cac-lop-co-ban-cua-mang-Convolutional-Neural-Network-75x75.webp 75w, https:\/\/interdata.vn\/blog\/wp-content\/uploads\/2025\/03\/Cac-lop-co-ban-cua-mang-Convolutional-Neural-Network-350x350.webp 350w, https:\/\/interdata.vn\/blog\/wp-content\/uploads\/2025\/03\/Cac-lop-co-ban-cua-mang-Convolutional-Neural-Network-750x748.webp 750w\" sizes=\"auto, (max-width: 770px) 100vw, 770px\" \/><figcaption id=\"caption-attachment-26079\" class=\"wp-caption-text\">C\u00e1c l\u1edbp c\u01a1 b\u1ea3n c\u1ee7a m\u1ea1ng Convolutional Neural Network<\/figcaption><\/figure>\n<h3><span class=\"ez-toc-section\" id=\"Lop-gop-Pooling-Layer\"><\/span>L\u1edbp g\u1ed9p (Pooling Layer)<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p>Khi k\u00edch th\u01b0\u1edbc \u0111\u1ea7u v\u00e0o qu\u00e1 l\u1edbn, c\u00e1c <strong>l\u1edbp g\u1ed9p (pooling layer)<\/strong> \u0111\u01b0\u1ee3c s\u1eed d\u1ee5ng \u0111\u1ec3 <strong>gi\u1ea3m s\u1ed1 l\u01b0\u1ee3ng tham s\u1ed1<\/strong> v\u00e0 <strong>t\u00ednh to\u00e1n<\/strong> trong m\u1ea1ng. L\u1edbp pooling th\u01b0\u1eddng \u0111\u01b0\u1ee3c \u0111\u1eb7t xen k\u1ebd gi\u1eefa c\u00e1c l\u1edbp t\u00edch ch\u1eadp.<\/p>\n<p>C\u00f3 hai lo\u1ea1i pooling ph\u1ed5 bi\u1ebfn: <strong>max pooling<\/strong> (l\u1ea5y gi\u00e1 tr\u1ecb l\u1edbn nh\u1ea5t trong m\u1ed9t v\u00f9ng) v\u00e0 <strong>average pooling<\/strong> (l\u1ea5y gi\u00e1 tr\u1ecb trung b\u00ecnh trong m\u1ed9t v\u00f9ng). Pooling gi\u00fap gi\u1ea3m chi\u1ec1u d\u1eef li\u1ec7u, t\u0103ng t\u00ednh b\u1ea5t bi\u1ebfn v\u1edbi c\u00e1c thay \u0111\u1ed5i nh\u1ecf trong h\u00ecnh \u1ea3nh, v\u00e0 gi\u1ea3m nguy c\u01a1 overfitting (qu\u00e1 kh\u1edbp).<\/p>\n<h3><span class=\"ez-toc-section\" id=\"Lop-ket-noi-day-du-Fully-Connected-Layer\"><\/span>L\u1edbp k\u1ebft n\u1ed1i \u0111\u1ea7y \u0111\u1ee7 (Fully Connected Layer)<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p>Sau c\u00e1c b\u01b0\u1edbc Convolution v\u00e0 Pooling, ch\u00fang ta thu \u0111\u01b0\u1ee3c th\u00f4ng tin c\u1ee7a \u1ea3nh \u1edf d\u1ea1ng \u0111\u00e3 \u0111\u01b0\u1ee3c x\u1eed l\u00fd. L\u1edbp k\u1ebft n\u1ed1i \u0111\u1ea7y \u0111\u1ee7 (fully connected layer) c\u00f3 nhi\u1ec7m v\u1ee5 <strong>k\u1ebft n\u1ed1i t\u1ea5t c\u1ea3 c\u00e1c n\u01a1-ron<\/strong> t\u1eeb l\u1edbp tr\u01b0\u1edbc \u0111\u1ebfn t\u1ea5t c\u1ea3 c\u00e1c n\u01a1-ron \u1edf l\u1edbp ti\u1ebfp theo.<\/p>\n<p>L\u1edbp k\u1ebft n\u1ed1i \u0111\u00f3ng vai tr\u00f2 nh\u01b0 m\u1ed9t b\u1ed9 ph\u00e2n lo\u1ea1i (classifier), s\u1eed d\u1ee5ng c\u00e1c \u0111\u1eb7c tr\u01b0ng \u0111\u00e3 \u0111\u01b0\u1ee3c tr\u00edch xu\u1ea5t \u0111\u1ec3 \u0111\u01b0a ra d\u1ef1 \u0111o\u00e1n cu\u1ed1i c\u00f9ng. N\u1ebfu l\u1edbp n\u00e0y nh\u1eadn \u0111\u01b0\u1ee3c data v\u1ec1 \u1ea3nh th\u00ec ch\u00fang s\u1ebd chuy\u1ec3n data \u0111\u00f3 th\u00e0nh 1 m\u1ee5c ch\u01b0a ph\u00e2n lo\u1ea1i.<\/p>\n<h2><span class=\"ez-toc-section\" id=\"Thuat-toan-CNN-co-cau-truc-nhu-the-nao\"><\/span>Thu\u1eadt to\u00e1n CNN c\u00f3 c\u1ea5u tr\u00fac nh\u01b0 th\u1ebf n\u00e0o?<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>M\u1ea1ng CNN (Convolutional Neural Network) v\u1ec1 b\u1ea3n ch\u1ea5t l\u00e0 m\u1ed9t <strong>chu\u1ed7i c\u00e1c l\u1edbp t\u00edch ch\u1eadp (convolutional layers) x\u1ebfp ch\u1ed3ng l\u00ean nhau<\/strong>. C\u00e1c l\u1edbp n\u00e0y \u0111\u01b0\u1ee3c k\u1ebft h\u1ee3p v\u1edbi c\u00e1c <strong>h\u00e0m k\u00edch ho\u1ea1t phi tuy\u1ebfn<\/strong> (nonlinear activation functions) nh\u01b0 ReLU (Rectified Linear Unit) ho\u1eb7c tanh, \u0111\u1ec3 \u0111i\u1ec1u ch\u1ec9nh tr\u1ecdng s\u1ed1 (weights) c\u1ee7a c\u00e1c k\u1ebft n\u1ed1i gi\u1eefa c\u00e1c n\u01a1-ron. Qu\u00e1 tr\u00ecnh n\u00e0y gi\u00fap m\u1ea1ng CNN h\u1ecdc v\u00e0 tr\u00edch xu\u1ea5t c\u00e1c \u0111\u1eb7c tr\u01b0ng ng\u00e0y c\u00e0ng tr\u1eebu t\u01b0\u1ee3ng t\u1eeb d\u1eef li\u1ec7u \u0111\u1ea7u v\u00e0o.<\/p>\n<p>M\u1ed9t \u0111i\u1ec3m \u0111\u1eb7c bi\u1ec7t c\u1ee7a CNN l\u00e0 t\u00ednh b\u1ea5t bi\u1ebfn (invariance) v\u00e0 t\u00ednh k\u1ebft h\u1ee3p c\u1ee5c b\u1ed9 (local connectivity). L\u1edbp pooling (g\u1ed9p) \u0111\u1ea3m b\u1ea3o t\u00ednh b\u1ea5t bi\u1ebfn \u0111\u1ed1i v\u1edbi c\u00e1c bi\u1ebfn \u0111\u1ed5i nh\u1ecf c\u1ee7a h\u00ecnh \u1ea3nh nh\u01b0 d\u1ecbch chuy\u1ec3n, xoay, ho\u1eb7c co gi\u00e3n, gi\u00fap CNN nh\u1eadn d\u1ea1ng \u0111\u1ed1i t\u01b0\u1ee3ng ch\u00ednh x\u00e1c h\u01a1n.<\/p>\n<p>T\u00ednh k\u1ebft h\u1ee3p c\u1ee5c b\u1ed9, th\u00f4ng qua c\u00e1c ph\u00e9p to\u00e1n t\u00edch ch\u1eadp (convolution), cho ph\u00e9p CNN bi\u1ec3u di\u1ec5n th\u00f4ng tin t\u1eeb m\u1ee9c \u0111\u1ed9 chi ti\u1ebft (c\u1ea1nh, g\u00f3c) \u0111\u1ebfn m\u1ee9c \u0111\u1ed9 t\u1ed5ng qu\u00e1t (h\u00ecnh d\u1ea1ng, \u0111\u1ed1i t\u01b0\u1ee3ng).<\/p>\n<figure id=\"attachment_26077\" aria-describedby=\"caption-attachment-26077\" style=\"width: 708px\" class=\"wp-caption aligncenter\"><img loading=\"lazy\" decoding=\"async\" src=\"https:\/\/interdata.vn\/blog\/wp-content\/uploads\/2025\/03\/Thuat-toan-CNN-co-cau-truc-nhu-the-nao.webp\" alt=\"Thu\u1eadt to\u00e1n CNN c\u00f3 c\u1ea5u tr\u00fac nh\u01b0 th\u1ebf n\u00e0o\" width=\"708\" height=\"353\" class=\"size-full wp-image-26077\" title=\"\" srcset=\"https:\/\/interdata.vn\/blog\/wp-content\/uploads\/2025\/03\/Thuat-toan-CNN-co-cau-truc-nhu-the-nao.webp 708w, https:\/\/interdata.vn\/blog\/wp-content\/uploads\/2025\/03\/Thuat-toan-CNN-co-cau-truc-nhu-the-nao-300x150.webp 300w, https:\/\/interdata.vn\/blog\/wp-content\/uploads\/2025\/03\/Thuat-toan-CNN-co-cau-truc-nhu-the-nao-360x180.webp 360w\" sizes=\"auto, (max-width: 708px) 100vw, 708px\" \/><figcaption id=\"caption-attachment-26077\" class=\"wp-caption-text\">Thu\u1eadt to\u00e1n CNN c\u00f3 c\u1ea5u tr\u00fac nh\u01b0 th\u1ebf n\u00e0o?<\/figcaption><\/figure>\n<p>Trong qu\u00e1 tr\u00ecnh hu\u1ea5n luy\u1ec7n, CNN <strong>t\u1ef1 \u0111\u1ed9ng h\u1ecdc c\u00e1c gi\u00e1 tr\u1ecb<\/strong> c\u1ee7a b\u1ed9 l\u1ecdc (filters) d\u1ef1a tr\u00ean d\u1eef li\u1ec7u hu\u1ea5n luy\u1ec7n, t\u01b0\u01a1ng t\u1ef1 nh\u01b0 c\u00e1ch con ng\u01b0\u1eddi h\u1ecdc c\u00e1ch nh\u1eadn bi\u1ebft c\u00e1c v\u1eadt th\u1ec3. M\u1ed7i l\u1edbp t\u00edch ch\u1eadp ti\u1ebfp theo s\u1ebd nh\u1eadn \u0111\u1ea7u v\u00e0o l\u00e0 k\u1ebft qu\u1ea3 (feature map) c\u1ee7a l\u1edbp tr\u01b0\u1edbc, t\u1ea1o ra m\u1ed9t h\u1ec7 th\u1ed1ng ph\u00e2n c\u1ea5p c\u00e1c \u0111\u1eb7c tr\u01b0ng.<\/p>\n<p>Ngo\u00e0i ra, l\u1edbp Pooling\/Subsampling c\u00f3 vai tr\u00f2<strong> l\u1ecdc b\u1edbt th\u00f4ng tin nhi\u1ec5u<\/strong>, gi\u1eef l\u1ea1i nh\u1eefng th\u00f4ng tin quan tr\u1ecdng.<\/p>\n<p>C\u1ea5u tr\u00fac c\u01a1 b\u1ea3n c\u1ee7a m\u1ed9t m\u1ea1ng CNN th\u01b0\u1eddng bao g\u1ed3m ba th\u00e0nh ph\u1ea7n ch\u00ednh:<\/p>\n<ul>\n<li><strong>Local Receptive Field:<\/strong> M\u1ed7i n\u01a1-ron trong l\u1edbp t\u00edch ch\u1eadp ch\u1ec9 k\u1ebft n\u1ed1i v\u1edbi m\u1ed9t v\u00f9ng nh\u1ecf c\u1ee7a h\u00ecnh \u1ea3nh \u0111\u1ea7u v\u00e0o (ho\u1eb7c feature map c\u1ee7a l\u1edbp tr\u01b0\u1edbc). \u0110i\u1ec1u n\u00e0y gi\u00fap CNN t\u1eadp trung v\u00e0o c\u00e1c \u0111\u1eb7c \u0111i\u1ec3m c\u1ee5c b\u1ed9 quan tr\u1ecdng.<\/li>\n<li><strong>Shared Weights and Bias:<\/strong> C\u00e1c n\u01a1-ron trong c\u00f9ng m\u1ed9t feature map s\u1eed d\u1ee5ng chung m\u1ed9t b\u1ed9 tr\u1ecdng s\u1ed1 (weights) v\u00e0 \u0111\u1ed9 l\u1ec7ch (bias). \u0110i\u1ec1u n\u00e0y gi\u00fap gi\u1ea3m \u0111\u00e1ng k\u1ec3 s\u1ed1 l\u01b0\u1ee3ng tham s\u1ed1 c\u1ea7n h\u1ecdc, l\u00e0m cho m\u00f4 h\u00ecnh hi\u1ec7u qu\u1ea3 h\u01a1n v\u00e0 gi\u1ea3m nguy c\u01a1 overfitting.<\/li>\n<li><strong>Pooling Layer:<\/strong> L\u1edbp n\u00e0y gi\u00fap gi\u1ea3m chi\u1ec1u d\u1eef li\u1ec7u, gi\u1ea3m t\u00ednh to\u00e1n v\u00e0 t\u0103ng t\u00ednh b\u1ea5t bi\u1ebfn c\u1ee7a m\u00f4 h\u00ecnh v\u1edbi c\u00e1c bi\u1ebfn \u0111\u1ed5i nh\u1ecf c\u1ee7a h\u00ecnh \u1ea3nh. N\u00f3 th\u1ef1c hi\u1ec7n vi\u1ec7c gi\u1ea3m chi\u1ec1u b\u1eb1ng c\u00e1ch l\u1ea5y gi\u00e1 tr\u1ecb l\u1edbn nh\u1ea5t (max pooling) ho\u1eb7c gi\u00e1 tr\u1ecb trung b\u00ecnh (average pooling) trong m\u1ed9t v\u00f9ng.<\/li>\n<\/ul>\n<h2><span class=\"ez-toc-section\" id=\"Uu-nhuoc-diem-cua-Convolutional-Neural-Network\"><\/span>\u01afu, nh\u01b0\u1ee3c \u0111i\u1ec3m c\u1ee7a Convolutional Neural Network<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<h3><span class=\"ez-toc-section\" id=\"Uu-diem-cua-CNN-la-gi\"><\/span>\u01afu \u0111i\u1ec3m c\u1ee7a CNN l\u00e0 g\u00ec?<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<ul>\n<li>Kh\u1ea3 n\u0103ng nh\u1eadn di\u1ec7n m\u1eabu v\u00e0 tr\u00edch xu\u1ea5t \u0111\u1eb7c tr\u01b0ng hi\u1ec7u qu\u1ea3 t\u1eeb h\u00ecnh \u1ea3nh, video v\u00e0 t\u00edn hi\u1ec7u \u00e2m thanh.<\/li>\n<li>Kh\u1ea3 n\u0103ng ch\u1ecbu \u0111\u01b0\u1ee3c s\u1ef1 thay \u0111\u1ed5i v\u1ec1 v\u1ecb tr\u00ed, xoay, v\u00e0 t\u1ef7 l\u1ec7 k\u00edch th\u01b0\u1edbc c\u1ee7a d\u1eef li\u1ec7u \u0111\u1ea7u v\u00e0o.<\/li>\n<li>H\u1ed7 tr\u1ee3 hu\u1ea5n luy\u1ec7n \u0111\u1ea7u-cu\u1ed1i (end-to-end), kh\u00f4ng c\u1ea7n tr\u00edch xu\u1ea5t \u0111\u1eb7c tr\u01b0ng th\u1ee7 c\u00f4ng.<\/li>\n<li>C\u00f3 th\u1ec3 x\u1eed l\u00fd l\u01b0\u1ee3ng <a href=\"https:\/\/interdata.vn\/blog\/big-data-la-gi\/\">d\u1eef li\u1ec7u l\u1edbn<\/a> v\u00e0 \u0111\u1ea1t \u0111\u1ed9 ch\u00ednh x\u00e1c cao.<\/li>\n<\/ul>\n<h3><span class=\"ez-toc-section\" id=\"Nhuoc-diem-cua-CNN-la-gi\"><\/span>Nh\u01b0\u1ee3c \u0111i\u1ec3m c\u1ee7a CNN l\u00e0 g\u00ec?<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<ul>\n<li>\u0110\u00f2i h\u1ecfi t\u00e0i nguy\u00ean t\u00ednh to\u00e1n l\u1edbn v\u00e0 b\u1ed9 nh\u1edb cao trong qu\u00e1 tr\u00ecnh hu\u1ea5n luy\u1ec7n.<\/li>\n<li>D\u1ec5 b\u1ecb overfitting (qu\u00e1 kh\u1edbp) n\u1ebfu d\u1eef li\u1ec7u kh\u00f4ng \u0111\u1ee7 l\u1edbn ho\u1eb7c kh\u00f4ng c\u00f3 k\u1ef9 thu\u1eadt \u0111i\u1ec1u chu\u1ea9n (regularization) ph\u00f9 h\u1ee3p.<\/li>\n<li>C\u1ea7n l\u01b0\u1ee3ng l\u1edbn d\u1eef li\u1ec7u c\u00f3 nh\u00e3n \u0111\u1ec3 hu\u1ea5n luy\u1ec7n.<\/li>\n<li>Kh\u1ea3 n\u0103ng gi\u1ea3i th\u00edch c\u00f2n h\u1ea1n ch\u1ebf, kh\u00f3 hi\u1ec3u \u0111\u01b0\u1ee3c m\u00f4 h\u00ecnh \u0111\u00e3 h\u1ecdc nh\u1eefng g\u00ec.<\/li>\n<\/ul>\n<h2><span class=\"ez-toc-section\" id=\"Su-khac-biet-giua-CNN-so-voi-mang-no-ron-truyen-thong\"><\/span>S\u1ef1 kh\u00e1c bi\u1ec7t gi\u1eefa CNN so v\u1edbi m\u1ea1ng n\u01a1-ron truy\u1ec1n th\u1ed1ng<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>M\u00f4 h\u00ecnh m\u1ea1ng n\u01a1-ron truy\u1ec1n th\u1ed1ng, th\u01b0\u1eddng \u0111\u01b0\u1ee3c bi\u1ebft \u0111\u1ebfn v\u1edbi t\u00ean g\u1ecdi <strong>Multilayer Perceptrons (MLP)<\/strong>, bao g\u1ed3m nhi\u1ec1u l\u1edbp k\u1ebft n\u1ed1i ho\u00e0n to\u00e0n (fully connected layers). D\u00f9 c\u00f3 t\u00ednh linh ho\u1ea1t, nh\u01b0ng ch\u00fang kh\u00f4ng \u0111\u01b0\u1ee3c t\u1ed1i \u01b0u h\u00f3a cho d\u1eef li\u1ec7u kh\u00f4ng gian nh\u01b0 h\u00ecnh \u1ea3nh, d\u1eabn \u0111\u1ebfn m\u1ed9t s\u1ed1 h\u1ea1n ch\u1ebf khi x\u1eed l\u00fd d\u1eef li\u1ec7u \u0111\u1ea7u v\u00e0o ph\u1ee9c t\u1ea1p v\u00e0 c\u00f3 k\u00edch th\u01b0\u1edbc l\u1edbn.<\/p>\n<p>V\u1edbi <strong>h\u00ecnh \u1ea3nh nh\u1ecf v\u00e0 \u00edt k\u00eanh m\u00e0u<\/strong>, m\u1ea1ng n\u01a1-ron truy\u1ec1n th\u1ed1ng c\u00f3 th\u1ec3 cho k\u1ebft qu\u1ea3 ch\u1ea5p nh\u1eadn \u0111\u01b0\u1ee3c. Tuy nhi\u00ean, khi k\u00edch th\u01b0\u1edbc v\u00e0 \u0111\u1ed9 ph\u1ee9c t\u1ea1p c\u1ee7a h\u00ecnh \u1ea3nh t\u0103ng l\u00ean, nhu c\u1ea7u v\u1ec1 t\u00e0i nguy\u00ean t\u00ednh to\u00e1n c\u0169ng t\u0103ng \u0111\u00e1ng k\u1ec3.<\/p>\n<p>M\u1ed9t v\u1ea5n \u0111\u1ec1 quan tr\u1ecdng kh\u00e1c l\u00e0 <strong>nguy c\u01a1 overfitting<\/strong>, v\u00ec ki\u1ebfn tr\u00fac fully connected kh\u00f4ng t\u1ef1 \u0111\u1ed9ng x\u00e1c \u0111\u1ecbnh \u0111\u1eb7c tr\u01b0ng quan tr\u1ecdng m\u00e0 c\u00f3 th\u1ec3 h\u1ecdc c\u1ea3 nhi\u1ec5u v\u00e0 th\u00f4ng tin kh\u00f4ng c\u1ea7n thi\u1ebft.<\/p>\n<p>CNNs c\u00f3 m\u1ed9t s\u1ed1 \u0111i\u1ec3m kh\u00e1c bi\u1ec7t ch\u00ednh so v\u1edbi m\u1ea1ng n\u01a1-ron truy\u1ec1n th\u1ed1ng:<\/p>\n<ul>\n<li>Trong CNN, kh\u00f4ng ph\u1ea3i t\u1ea5t c\u1ea3 c\u00e1c n\u00fat trong m\u1ed9t l\u1edbp \u0111\u1ec1u k\u1ebft n\u1ed1i v\u1edbi c\u00e1c n\u00fat c\u1ee7a l\u1edbp ti\u1ebfp theo. \u0110i\u1ec1u n\u00e0y gi\u00fap gi\u1ea3m s\u1ed1 l\u01b0\u1ee3ng tham s\u1ed1 v\u00e0 t\u0103ng hi\u1ec7u su\u1ea5t x\u1eed l\u00fd h\u00ecnh \u1ea3nh.<\/li>\n<li>CNN s\u1eed d\u1ee5ng k\u1ef9 thu\u1eadt chia s\u1ebb tham s\u1ed1 (parameter sharing) gi\u00fap t\u1ed1i \u01b0u h\u00f3a x\u1eed l\u00fd d\u1eef li\u1ec7u h\u00ecnh \u1ea3nh. Trong c\u00e1c l\u1edbp t\u00edch ch\u1eadp, c\u00f9ng m\u1ed9t b\u1ed9 l\u1ecdc (v\u1edbi tr\u1ecdng s\u1ed1 c\u1ed1 \u0111\u1ecbnh) qu\u00e9t to\u00e0n b\u1ed9 h\u00ecnh \u1ea3nh, gi\u00fap gi\u1ea3m \u0111\u00e1ng k\u1ec3 s\u1ed1 l\u01b0\u1ee3ng tham s\u1ed1 so v\u1edbi c\u00e1c l\u1edbp fully connected c\u1ee7a m\u1ea1ng n\u01a1-ron truy\u1ec1n th\u1ed1ng.<\/li>\n<li>L\u1edbp Pooling gi\u00fap gi\u1ea3m k\u00edch th\u01b0\u1edbc d\u1eef li\u1ec7u, t\u0103ng hi\u1ec7u su\u1ea5t x\u1eed l\u00fd v\u00e0 c\u1ea3i thi\u1ec7n kh\u1ea3 n\u0103ng t\u1ed5ng qu\u00e1t h\u00f3a c\u1ee7a m\u00f4 h\u00ecnh CNN.<\/li>\n<\/ul>\n<h2><span class=\"ez-toc-section\" id=\"Ung-dung-cua-Convolutional-Neural-Network\"><\/span>\u1ee8ng d\u1ee5ng c\u1ee7a Convolutional Neural Network<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>X\u1eed l\u00fd v\u00e0 ph\u00e2n t\u00edch d\u1eef li\u1ec7u h\u00ecnh \u1ea3nh l\u00e0 m\u1ed9t trong nh\u1eefng t\u00e1c v\u1ee5 ph\u1ed5 bi\u1ebfn, v\u00ec v\u1eady CNN \u0111\u01b0\u1ee3c \u1ee9ng d\u1ee5ng r\u1ed9ng r\u00e3i trong nhi\u1ec1u l\u0129nh v\u1ef1c th\u1ef1c t\u1ebf, t\u1eeb y t\u1ebf, \u00f4 t\u00f4 \u0111\u1ebfn m\u1ea1ng x\u00e3 h\u1ed9i v\u00e0 th\u01b0\u01a1ng m\u1ea1i \u0111i\u1ec7n t\u1eed. D\u01b0\u1edbi \u0111\u00e2y l\u00e0 c\u00e1c \u1ee9ng d\u1ee5ng chi ti\u1ebft \u0111\u1ec3 b\u1ea1n hi\u1ec3u r\u00f5 h\u01a1n Convolutional Neural Network l\u00e0 g\u00ec:<\/p>\n<h3><span class=\"ez-toc-section\" id=\"1-Y-te\"><\/span>1. Y t\u1ebf<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p>CNNs h\u1ed7 tr\u1ee3 <strong>ch\u1ea9n \u0111o\u00e1n y khoa v\u00e0 ph\u00e2n t\u00edch h\u00ecnh \u1ea3nh y t\u1ebf<\/strong>. V\u00ed d\u1ee5, CNN c\u00f3 th\u1ec3 ph\u00e2n t\u00edch \u1ea3nh X-quang, \u1ea3nh m\u00f4 b\u1ec7nh h\u1ecdc \u0111\u1ec3 ph\u00e1t hi\u1ec7n d\u1ea5u hi\u1ec7u b\u1ea5t th\u01b0\u1eddng c\u1ee7a b\u1ec7nh, h\u1ed7 tr\u1ee3 b\u00e1c s\u0129 trong vi\u1ec7c ch\u1ea9n \u0111o\u00e1n v\u00e0 l\u00ean k\u1ebf ho\u1ea1ch \u0111i\u1ec1u tr\u1ecb.<\/p>\n<h3><span class=\"ez-toc-section\" id=\"2-O-to\"><\/span>2. \u00d4 t\u00f4<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p>Ng\u00e0nh c\u00f4ng nghi\u1ec7p \u00f4 t\u00f4 \u1ee9ng d\u1ee5ng CNN trong xe t\u1ef1 h\u00e0nh \u0111\u1ec3 <strong>nh\u1eadn di\u1ec7n m\u00f4i tr\u01b0\u1eddng xung quanh<\/strong> th\u00f4ng qua d\u1eef li\u1ec7u t\u1eeb camera v\u00e0 c\u1ea3m bi\u1ebfn. Ngo\u00e0i ra, CNN c\u00f2n \u0111\u01b0\u1ee3c t\u00edch h\u1ee3p v\u00e0o c\u00e1c t\u00ednh n\u0103ng h\u1ed7 tr\u1ee3 l\u00e1i xe nh\u01b0 ki\u1ec3m so\u00e1t h\u00e0nh tr\u00ecnh t\u1ef1 \u0111\u1ed9ng, h\u1ed7 tr\u1ee3 \u0111\u1ed7 xe.<\/p>\n<figure id=\"attachment_26078\" aria-describedby=\"caption-attachment-26078\" style=\"width: 1000px\" class=\"wp-caption aligncenter\"><img loading=\"lazy\" decoding=\"async\" src=\"https:\/\/interdata.vn\/blog\/wp-content\/uploads\/2025\/03\/Ung-dung-cua-Convolutional-Neural-Network.jpg\" alt=\"\u1ee8ng d\u1ee5ng c\u1ee7a Convolutional Neural Network\" width=\"1000\" height=\"340\" class=\"size-full wp-image-26078\" title=\"\" srcset=\"https:\/\/interdata.vn\/blog\/wp-content\/uploads\/2025\/03\/Ung-dung-cua-Convolutional-Neural-Network.jpg 1000w, https:\/\/interdata.vn\/blog\/wp-content\/uploads\/2025\/03\/Ung-dung-cua-Convolutional-Neural-Network-300x102.jpg 300w, https:\/\/interdata.vn\/blog\/wp-content\/uploads\/2025\/03\/Ung-dung-cua-Convolutional-Neural-Network-768x261.jpg 768w, https:\/\/interdata.vn\/blog\/wp-content\/uploads\/2025\/03\/Ung-dung-cua-Convolutional-Neural-Network-750x255.jpg 750w\" sizes=\"auto, (max-width: 1000px) 100vw, 1000px\" \/><figcaption id=\"caption-attachment-26078\" class=\"wp-caption-text\">\u1ee8ng d\u1ee5ng c\u1ee7a Convolutional Neural Network<\/figcaption><\/figure>\n<h3><span class=\"ez-toc-section\" id=\"3-Mang-xa-hoi\"><\/span>3. M\u1ea1ng x\u00e3 h\u1ed9i<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p>CNN \u0111\u01b0\u1ee3c s\u1eed d\u1ee5ng \u0111\u1ec3 <strong>ph\u00e2n t\u00edch h\u00ecnh \u1ea3nh tr\u00ean c\u00e1c n\u1ec1n t\u1ea3ng m\u1ea1ng x\u00e3 h\u1ed9i<\/strong>. V\u00ed d\u1ee5, c\u00e1c n\u1ec1n t\u1ea3ng n\u00e0y c\u00f3 th\u1ec3 d\u00f9ng CNN \u0111\u1ec3 nh\u1eadn di\u1ec7n khu\u00f4n m\u1eb7t v\u00e0 g\u1ee3i \u00fd g\u1eafn th\u1ebb (tag) b\u1ea1n b\u00e8 trong \u1ea3nh ho\u1eb7c ph\u00e1t hi\u1ec7n n\u1ed9i dung vi ph\u1ea1m ch\u00ednh s\u00e1ch \u0111\u1ec3 ki\u1ec3m duy\u1ec7t.<\/p>\n<h3><span class=\"ez-toc-section\" id=\"4-Thuong-mai-dien-tu\"><\/span>4. Th\u01b0\u01a1ng m\u1ea1i \u0111i\u1ec7n t\u1eed<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p>C\u00e1c trang th\u01b0\u01a1ng m\u1ea1i \u0111i\u1ec7n t\u1eed s\u1eed d\u1ee5ng CNN \u0111\u1ec3 ph\u00e1t tri\u1ec3n h\u1ec7 th\u1ed1ng t\u00ecm ki\u1ebfm b\u1eb1ng h\u00ecnh \u1ea3nh, cho ph\u00e9p ng\u01b0\u1eddi d\u00f9ng t\u00ecm s\u1ea3n ph\u1ea9m b\u1eb1ng c\u00e1ch t\u1ea3i l\u00ean h\u00ecnh \u1ea3nh thay v\u00ec nh\u1eadp v\u0103n b\u1ea3n.<\/p>\n<p>Ngo\u00e0i ra, CNN c\u00f2n gi\u00fap c\u1ea3i thi\u1ec7n h\u1ec7 th\u1ed1ng \u0111\u1ec1 xu\u1ea5t s\u1ea3n ph\u1ea9m d\u1ef1a tr\u00ean s\u1ef1 t\u01b0\u01a1ng \u0111\u1ed3ng v\u1ec1 h\u00ecnh \u1ea3nh v\u1edbi nh\u1eefng s\u1ea3n ph\u1ea9m m\u00e0 kh\u00e1ch h\u00e0ng quan t\u00e2m.<\/p>\n<h3><span class=\"ez-toc-section\" id=\"5-Tro-ly-ao\"><\/span>5. Tr\u1ee3 l\u00fd \u1ea3o<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p>D\u00f9 CNN ch\u1ee7 y\u1ebfu \u0111\u01b0\u1ee3c s\u1eed d\u1ee5ng cho d\u1eef li\u1ec7u h\u00ecnh \u1ea3nh, nh\u01b0ng ch\u00fang c\u0169ng c\u00f3 th\u1ec3 <strong>\u00e1p d\u1ee5ng v\u00e0o x\u1eed l\u00fd \u00e2m thanh<\/strong>. C\u00e1c <a href=\"https:\/\/interdata.vn\/blog\/tro-ly-ao-la-gi\/\">tr\u1ee3 l\u00fd \u1ea3o<\/a> nh\u01b0 Google Assistant, Siri c\u00f3 th\u1ec3 d\u00f9ng CNN \u0111\u1ec3 nh\u1eadn di\u1ec7n t\u1eeb kh\u00f3a trong gi\u1ecdng n\u00f3i, gi\u00fap hi\u1ec3u v\u00e0 ph\u1ea3n h\u1ed3i ch\u00ednh x\u00e1c h\u01a1n.<\/p>\n<p>CNN kh\u00f4ng ch\u1ec9 l\u00e0 m\u1ed9t trong nh\u1eefng b\u01b0\u1edbc ti\u1ebfn quan tr\u1ecdng trong l\u0129nh v\u1ef1c tr\u00ed tu\u1ec7 nh\u00e2n t\u1ea1o, m\u00e0 c\u00f2n l\u00e0 n\u1ec1n t\u1ea3ng cho nhi\u1ec1u c\u00f4ng ngh\u1ec7 ti\u00ean ti\u1ebfn trong \u0111\u1eddi s\u1ed1ng hi\u1ec7n \u0111\u1ea1i. V\u1edbi kh\u1ea3 n\u0103ng x\u1eed l\u00fd m\u1ea1nh m\u1ebd v\u00e0 \u1ee9ng d\u1ee5ng r\u1ed9ng r\u00e3i, CNN \u0111ang ng\u00e0y c\u00e0ng ch\u1ee9ng minh \u0111\u01b0\u1ee3c vai tr\u00f2 quan tr\u1ecdng trong nhi\u1ec1u l\u0129nh v\u1ef1c kh\u00e1c nhau.<\/p>\n<h2><span class=\"ez-toc-section\" id=\"Cach-chon-tham-so-cho-Convolutional-Neural-Network-CNN\"><\/span>C\u00e1ch ch\u1ecdn tham s\u1ed1 cho Convolutional Neural Network (CNN)<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>Vi\u1ec7c l\u1ef1a ch\u1ecdn tham s\u1ed1 cho m\u1ea1ng CNN l\u00e0 m\u1ed9t qu\u00e1 tr\u00ecnh quan tr\u1ecdng, \u1ea3nh h\u01b0\u1edfng tr\u1ef1c ti\u1ebfp \u0111\u1ebfn hi\u1ec7u su\u1ea5t c\u1ee7a m\u00f4 h\u00ecnh. Kh\u00f4ng c\u00f3 m\u1ed9t c\u00f4ng th\u1ee9c c\u1ed1 \u0111\u1ecbnh n\u00e0o, m\u00e0 c\u1ea7n d\u1ef1a tr\u00ean kinh nghi\u1ec7m, th\u1eed nghi\u1ec7m v\u00e0 \u0111i\u1ec1u ch\u1ec9nh.<\/p>\n<p>D\u01b0\u1edbi \u0111\u00e2y l\u00e0 m\u1ed9t s\u1ed1 h\u01b0\u1edbng d\u1eabn v\u00e0 ph\u01b0\u01a1ng ph\u00e1p th\u01b0\u1eddng \u0111\u01b0\u1ee3c s\u1eed d\u1ee5ng:<\/p>\n<ul>\n<li><strong>Ki\u1ebfn tr\u00fac m\u00f4 h\u00ecnh (Model Architecture):<\/strong> L\u1ef1a ch\u1ecdn ki\u1ebfn tr\u00fac ph\u00f9 h\u1ee3p v\u1edbi b\u00e0i to\u00e1n c\u1ee5 th\u1ec3. C\u1ea7n xem x\u00e9t s\u1ed1 l\u01b0\u1ee3ng l\u1edbp t\u00edch ch\u1eadp, s\u1ed1 l\u01b0\u1ee3ng l\u1edbp g\u1ed9p (pooling), s\u1ed1 l\u01b0\u1ee3ng n\u01a1-ron trong c\u00e1c l\u1edbp k\u1ebft n\u1ed1i \u0111\u1ea7y \u0111\u1ee7 (fully connected layers), k\u00edch th\u01b0\u1edbc v\u00e0 b\u01b0\u1edbc nh\u1ea3y (stride) c\u1ee7a b\u1ed9 l\u1ecdc, c\u0169ng nh\u01b0 c\u00e1c k\u1ef9 thu\u1eadt nh\u01b0 <a href=\"https:\/\/interdata.vn\/blog\/dropout-la-gi\/\">dropout<\/a> v\u00e0 <a href=\"https:\/\/interdata.vn\/blog\/batch-normalization-la-gi\/\">batch normalization<\/a>.<\/li>\n<li><strong>T\u1ed1c \u0111\u1ed9 h\u1ecdc (<a href=\"https:\/\/interdata.vn\/blog\/learning-rate-la-gi\/\">Learning Rate<\/a>):<\/strong> \u0110i\u1ec1u ch\u1ec9nh t\u1ed1c \u0111\u1ed9 h\u1ecdc l\u00e0 r\u1ea5t quan tr\u1ecdng. T\u1ed1c \u0111\u1ed9 h\u1ecdc qu\u00e1 cao c\u00f3 th\u1ec3 khi\u1ebfn m\u00f4 h\u00ecnh kh\u00f4ng h\u1ed9i t\u1ee5, trong khi t\u1ed1c \u0111\u1ed9 h\u1ecdc qu\u00e1 th\u1ea5p c\u00f3 th\u1ec3 khi\u1ebfn qu\u00e1 tr\u00ecnh hu\u1ea5n luy\u1ec7n di\u1ec5n ra ch\u1eadm ch\u1ea1p. Th\u01b0\u1eddng b\u1eaft \u0111\u1ea7u v\u1edbi m\u1ed9t gi\u00e1 tr\u1ecb nh\u1ecf (v\u00ed d\u1ee5: 0.001) v\u00e0 \u0111i\u1ec1u ch\u1ec9nh d\u1ea7n.<\/li>\n<li><strong>Thu\u1eadt to\u00e1n t\u1ed1i \u01b0u h\u00f3a (Optimization Algorithm):<\/strong> L\u1ef1a ch\u1ecdn thu\u1eadt to\u00e1n t\u1ed1i \u01b0u h\u00f3a ph\u00f9 h\u1ee3p, nh\u01b0 Adam, SGD (Stochastic <a href=\"https:\/\/interdata.vn\/blog\/gradient-descent-la-gi\/\">Gradient Descent<\/a>), RMSprop, \u0111\u1ec3 c\u1eadp nh\u1eadt tr\u1ecdng s\u1ed1 c\u1ee7a m\u1ea1ng trong qu\u00e1 tr\u00ecnh hu\u1ea5n luy\u1ec7n. M\u1ed7i thu\u1eadt to\u00e1n c\u00f3 \u01b0u v\u00e0 nh\u01b0\u1ee3c \u0111i\u1ec3m ri\u00eang.<\/li>\n<li><strong>K\u00edch th\u01b0\u1edbc batch (Batch Size):<\/strong> K\u00edch th\u01b0\u1edbc batch \u1ea3nh h\u01b0\u1edfng \u0111\u1ebfn t\u1ed1c \u0111\u1ed9 hu\u1ea5n luy\u1ec7n v\u00e0 kh\u1ea3 n\u0103ng t\u1ed5ng qu\u00e1t h\u00f3a c\u1ee7a m\u00f4 h\u00ecnh. C\u1ea7n c\u00e2n b\u1eb1ng gi\u1eefa vi\u1ec7c c\u1eadp nh\u1eadt tr\u1ecdng s\u1ed1 th\u01b0\u1eddng xuy\u00ean (batch size nh\u1ecf) v\u00e0 t\u1eadn d\u1ee5ng kh\u1ea3 n\u0103ng t\u00ednh to\u00e1n song song c\u1ee7a ph\u1ea7n c\u1ee9ng (batch size l\u1edbn).<\/li>\n<li><strong>H\u00e0m k\u00edch ho\u1ea1t (Activation Function):<\/strong> L\u1ef1a ch\u1ecdn h\u00e0m k\u00edch ho\u1ea1t ph\u00f9 h\u1ee3p cho c\u00e1c l\u1edbp. ReLU th\u01b0\u1eddng \u0111\u01b0\u1ee3c s\u1eed d\u1ee5ng cho c\u00e1c l\u1edbp \u1ea9n, trong khi Sigmoid ho\u1eb7c Tanh c\u00f3 th\u1ec3 \u0111\u01b0\u1ee3c s\u1eed d\u1ee5ng cho l\u1edbp \u0111\u1ea7u ra (t\u00f9y thu\u1ed9c v\u00e0o b\u00e0i to\u00e1n). Leaky ReLU l\u00e0 m\u1ed9t bi\u1ebfn th\u1ec3 c\u1ee7a ReLU c\u0169ng th\u01b0\u1eddng \u0111\u01b0\u1ee3c s\u1eed d\u1ee5ng.<\/li>\n<li><strong>Kh\u1edfi t\u1ea1o tr\u1ecdng s\u1ed1 (Weight Initialization):<\/strong> C\u00e1ch kh\u1edfi t\u1ea1o tr\u1ecdng s\u1ed1 ban \u0111\u1ea7u c\u00f3 th\u1ec3 \u1ea3nh h\u01b0\u1edfng \u0111\u1ebfn t\u1ed1c \u0111\u1ed9 h\u1ed9i t\u1ee5 v\u00e0 hi\u1ec7u su\u1ea5t c\u1ee7a m\u00f4 h\u00ecnh. C\u00e1c ph\u01b0\u01a1ng ph\u00e1p ph\u1ed5 bi\u1ebfn bao g\u1ed3m Xavier, He, v\u00e0 Glorot.<\/li>\n<li><strong>Ki\u1ec3m tra v\u00e0 \u0111\u00e1nh gi\u00e1 (Testing and Evaluation):<\/strong> S\u1eed d\u1ee5ng c\u00e1c k\u1ef9 thu\u1eadt nh\u01b0 cross-validation (ki\u1ec3m tra ch\u00e9o) v\u00e0 early stopping (d\u1eebng s\u1edbm) \u0111\u1ec3 \u0111\u00e1nh gi\u00e1 hi\u1ec7u su\u1ea5t c\u1ee7a m\u00f4 h\u00ecnh v\u00e0 tr\u00e1nh overfitting (qu\u00e1 kh\u1edbp v\u1edbi d\u1eef li\u1ec7u hu\u1ea5n luy\u1ec7n).<\/li>\n<\/ul>\n<p>CNN l\u00e0 m\u1ed9t b\u01b0\u1edbc ti\u1ebfn quan tr\u1ecdng trong l\u0129nh v\u1ef1c AI, gi\u00fap t\u1ed1i \u01b0u h\u00f3a vi\u1ec7c x\u1eed l\u00fd h\u00ecnh \u1ea3nh v\u00e0 nh\u1eadn di\u1ec7n \u0111\u1ed1i t\u01b0\u1ee3ng v\u1edbi \u0111\u1ed9 ch\u00ednh x\u00e1c cao. Hi\u1ec3u r\u00f5 v\u1ec1 c\u1ea5u tr\u00fac, \u1ee9ng d\u1ee5ng c\u1ee7a <strong>Convolutional Neural Network l\u00e0 g\u00ec<\/strong> v\u00e0 c\u00e1ch ch\u1ecdn tham s\u1ed1 ph\u00f9 h\u1ee3p s\u1ebd gi\u00fap b\u1ea1n \u1ee9ng d\u1ee5ng thu\u1eadt to\u00e1n CNN m\u1ed9t c\u00e1ch hi\u1ec7u qu\u1ea3 v\u00e0o c\u00e1c b\u00e0i to\u00e1n th\u1ef1c t\u1ebf.<\/p>\n<p>X\u1eed l\u00fd h\u00ecnh \u1ea3nh b\u1eb1ng Convolutional Neural Network (CNN) \u0111\u00f2i h\u1ecfi m\u1ed9t h\u1ec7 th\u1ed1ng <a href=\"https:\/\/interdata.vn\/blog\/may-chu-server-la-gi\/\">m\u00e1y ch\u1ee7<\/a> m\u1ea1nh m\u1ebd v\u1edbi t\u1ed1c \u0111\u1ed9 x\u1eed l\u00fd cao v\u00e0 b\u0103ng th\u00f4ng l\u1edbn. D\u1ecbch v\u1ee5 <a href=\"https:\/\/interdata.vn\/thue-vps\/\">thu\u00ea VPS Vi\u1ec7t Nam ch\u1ea5t l\u01b0\u1ee3ng cao gi\u00e1 r\u1ebb<\/a> t\u1ea1i <a href=\"https:\/\/interdata.vn\/\">InterData<\/a> mang \u0111\u1ebfn gi\u1ea3i ph\u00e1p t\u1ed1i \u01b0u v\u1edbi <a href=\"https:\/\/interdata.vn\/blog\/cpu-server\/\">CPU<\/a> AMD EPYC\/Intel Xeon Platinum v\u00e0 \u1ed5 SSD NVMe U.2, gi\u00fap t\u1ed1i \u01b0u h\u00f3a qu\u00e1 tr\u00ecnh hu\u1ea5n luy\u1ec7n v\u00e0 tri\u1ec3n khai m\u00f4 h\u00ecnh CNN tr\u00ean n\u1ec1n t\u1ea3ng <a href=\"https:\/\/interdata.vn\/blog\/cloud-computing-la-gi\/\">\u0111i\u1ec7n to\u00e1n \u0111\u00e1m m\u00e2y<\/a>.<\/p>\n<p>N\u1ebfu b\u1ea1n c\u1ea7n h\u1ea1 t\u1ea7ng m\u00e1y ch\u1ee7 linh ho\u1ea1t h\u01a1n \u0111\u1ec3 x\u1eed l\u00fd d\u1eef li\u1ec7u l\u1edbn, <a href=\"https:\/\/interdata.vn\/cloud-server\/\">thu\u00ea Cloud Server gi\u00e1 r\u1ebb t\u1ed1c \u0111\u1ed9 cao<\/a> t\u1ea1i InterData l\u00e0 l\u1ef1a ch\u1ecdn \u0111\u00e1ng c\u00e2n nh\u1eafc. V\u1edbi ph\u1ea7n c\u1ee9ng th\u1ebf h\u1ec7 m\u1edbi, dung l\u01b0\u1ee3ng t\u1ed1i \u01b0u v\u00e0 kh\u1ea3 n\u0103ng m\u1edf r\u1ed9ng m\u1ea1nh m\u1ebd, Cloud Server gi\u00fap t\u0103ng t\u1ed1c qu\u00e1 tr\u00ecnh t\u00ednh to\u00e1n c\u1ee7a CNN, \u0111\u1ea3m b\u1ea3o hi\u1ec7u su\u1ea5t \u1ed5n \u0111\u1ecbnh v\u00e0 t\u1ed1i \u01b0u chi ph\u00ed v\u1eadn h\u00e0nh.<\/p>\n<p><strong>INTERDATA<\/strong><\/p>\n<ul>\n<li><strong>Website:<\/strong>\u00a0Interdata.vn<\/li>\n<li><strong>Hotline:<\/strong>\u00a01900-636822<\/li>\n<li><strong>Email:<\/strong>\u00a0Info@interdata.vn<\/li>\n<li><strong>VP\u0110D:<\/strong>\u00a0240 Nguy\u1ec5n \u0110\u00ecnh Ch\u00ednh, P.11. Q. Ph\u00fa Nhu\u1eadn, TP. Ho\u0302\u0300 Ch\u00ed Minh<\/li>\n<li><strong>VPGD:<\/strong>\u00a0S\u1ed1 211 \u0110\u01b0\u1eddng s\u1ed1 5, K\u0110T Lakeview City, P. An Ph\u00fa, TP. Th\u1ee7 \u0110\u1ee9c, TP. H\u1ed3 Ch\u00ed Minh<\/li>\n<\/ul>\n","protected":false},"excerpt":{"rendered":"<p>Trong l\u0129nh v\u1ef1c tr\u00ed tu\u1ec7 nh\u00e2n t\u1ea1o (AI), Convolutional Neural Network (CNN) l\u00e0 m\u1ed9t thu\u1eadt to\u00e1n h\u1ecdc s\u00e2u (Deep Learning) \u0111\u1eb7c bi\u1ec7t hi\u1ec7u qu\u1ea3 trong x\u1eed l\u00fd h\u00ecnh \u1ea3nh v\u00e0 nh\u1eadn di\u1ec7n \u0111\u1ed1i t\u01b0\u1ee3ng. CNN c\u00f3 kh\u1ea3 n\u0103ng t\u1ef1 \u0111\u1ed9ng h\u1ecdc c\u00e1c \u0111\u1eb7c tr\u01b0ng t\u1eeb d\u1eef li\u1ec7u, gi\u00fap c\u1ea3i thi\u1ec7n \u0111\u1ed9 ch\u00ednh x\u00e1c v\u00e0 t\u1ed1i<\/p>\n","protected":false},"author":11,"featured_media":26108,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[108],"tags":[125],"class_list":["post-26068","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-ai","tag-cnn"],"_links":{"self":[{"href":"https:\/\/interdata.vn\/blog\/wp-json\/wp\/v2\/posts\/26068","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/interdata.vn\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/interdata.vn\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/interdata.vn\/blog\/wp-json\/wp\/v2\/users\/11"}],"replies":[{"embeddable":true,"href":"https:\/\/interdata.vn\/blog\/wp-json\/wp\/v2\/comments?post=26068"}],"version-history":[{"count":1,"href":"https:\/\/interdata.vn\/blog\/wp-json\/wp\/v2\/posts\/26068\/revisions"}],"predecessor-version":[{"id":26105,"href":"https:\/\/interdata.vn\/blog\/wp-json\/wp\/v2\/posts\/26068\/revisions\/26105"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/interdata.vn\/blog\/wp-json\/wp\/v2\/media\/26108"}],"wp:attachment":[{"href":"https:\/\/interdata.vn\/blog\/wp-json\/wp\/v2\/media?parent=26068"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/interdata.vn\/blog\/wp-json\/wp\/v2\/categories?post=26068"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/interdata.vn\/blog\/wp-json\/wp\/v2\/tags?post=26068"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}