{"id":478247,"date":"2023-08-09T09:29:44","date_gmt":"2023-08-09T09:29:44","guid":{"rendered":""},"modified":"2023-09-05T11:16:21","modified_gmt":"2023-09-05T11:16:21","slug":"object-recognition","status":"publish","type":"wiki","link":"https:\/\/oneproxy.pro\/vn\/wiki\/object-recognition\/","title":{"rendered":"Nh\u1eadn d\u1ea1ng \u0111\u1ed1i t\u01b0\u1ee3ng"},"content":{"rendered":"<p>Th\u00f4ng tin t\u00f3m t\u1eaft v\u1ec1 nh\u1eadn d\u1ea1ng \u0111\u1ed1i t\u01b0\u1ee3ng<\/p>\n<p>Nh\u1eadn d\u1ea1ng \u0111\u1ed1i t\u01b0\u1ee3ng l\u00e0 c\u00f4ng ngh\u1ec7 \u0111\u01b0\u1ee3c s\u1eed d\u1ee5ng trong th\u1ecb gi\u00e1c m\u00e1y t\u00ednh cho ph\u00e9p m\u00e1y x\u00e1c \u0111\u1ecbnh v\u00e0 ph\u00e2n lo\u1ea1i \u0111\u1ed1i t\u01b0\u1ee3ng trong h\u00ecnh \u1ea3nh ho\u1eb7c video. Qu\u00e1 tr\u00ecnh n\u00e0y b\u1eaft ch\u01b0\u1edbc t\u1ea7m nh\u00ecn c\u1ee7a con ng\u01b0\u1eddi v\u00e0 \u0111\u01b0\u1ee3c s\u1eed d\u1ee5ng trong nhi\u1ec1u \u1ee9ng d\u1ee5ng kh\u00e1c nhau, ch\u1eb3ng h\u1ea1n nh\u01b0 robot, an ninh, ch\u0103m s\u00f3c s\u1ee9c kh\u1ecfe v\u00e0 xe t\u1ef1 h\u00e0nh.<\/p>\n<h2>L\u1ecbch s\u1eed ngu\u1ed3n g\u1ed1c c\u1ee7a c\u00f4ng ngh\u1ec7 nh\u1eadn d\u1ea1ng \u0111\u1ed1i t\u01b0\u1ee3ng v\u00e0 s\u1ef1 \u0111\u1ec1 c\u1eadp \u0111\u1ea7u ti\u00ean v\u1ec1 n\u00f3<\/h2>\n<p>Nh\u1eadn d\u1ea1ng \u0111\u1ed1i t\u01b0\u1ee3ng c\u00f3 t\u1eeb \u0111\u1ea7u nh\u1eefng n\u0103m 1960 khi c\u00e1c nh\u00e0 khoa h\u1ecdc b\u1eaft \u0111\u1ea7u nghi\u00ean c\u1ee9u kh\u1ea3 n\u0103ng b\u1eaft ch\u01b0\u1edbc nh\u1eadn th\u1ee9c c\u1ee7a con ng\u01b0\u1eddi b\u1eb1ng m\u00e1y t\u00ednh. Nh\u1eefng n\u1ed7 l\u1ef1c ban \u0111\u1ea7u c\u00f2n h\u1ea1n ch\u1ebf nh\u01b0ng \u0111\u00e3 \u0111\u1eb7t n\u1ec1n m\u00f3ng cho th\u1ee9 m\u00e0 cu\u1ed1i c\u00f9ng s\u1ebd tr\u1edf th\u00e0nh m\u1ed9t c\u00f4ng ngh\u1ec7 ph\u1ee9c t\u1ea1p v\u00e0 hi\u1ec7u qu\u1ea3 cao. Thu\u1eadt ng\u1eef \u201cNh\u1eadn d\u1ea1ng \u0111\u1ed1i t\u01b0\u1ee3ng\u201d l\u1ea7n \u0111\u1ea7u ti\u00ean xu\u1ea5t hi\u1ec7n trong t\u00e0i li\u1ec7u khoa h\u1ecdc trong th\u1eddi gian n\u00e0y, khi c\u00e1c nh\u00e0 nghi\u00ean c\u1ee9u t\u00ecm c\u00e1ch x\u00e1c \u0111\u1ecbnh c\u00e1c thu\u1eadt to\u00e1n c\u00f3 th\u1ec3 ph\u00e1t hi\u1ec7n c\u00e1c h\u00ecnh d\u1ea1ng v\u00e0 m\u1eabu \u0111\u01a1n gi\u1ea3n.<\/p>\n<h2>Th\u00f4ng tin chi ti\u1ebft v\u1ec1 nh\u1eadn d\u1ea1ng \u0111\u1ed1i t\u01b0\u1ee3ng: M\u1edf r\u1ed9ng ch\u1ee7 \u0111\u1ec1 nh\u1eadn d\u1ea1ng \u0111\u1ed1i t\u01b0\u1ee3ng<\/h2>\n<p>Nh\u1eadn d\u1ea1ng \u0111\u1ed1i t\u01b0\u1ee3ng bao g\u1ed3m m\u1ed9t s\u1ed1 giai \u0111o\u1ea1n, bao g\u1ed3m ti\u1ec1n x\u1eed l\u00fd, tr\u00edch xu\u1ea5t t\u00ednh n\u0103ng v\u00e0 ph\u00e2n lo\u1ea1i. C\u00e1c ph\u01b0\u01a1ng ph\u00e1p hi\u1ec7n \u0111\u1ea1i s\u1eed d\u1ee5ng m\u1ea1ng l\u01b0\u1edbi th\u1ea7n kinh v\u00e0 h\u1ecdc s\u00e2u \u0111\u1ec3 nh\u1eadn d\u1ea1ng \u0111\u1ed1i t\u01b0\u1ee3ng, s\u1eed d\u1ee5ng l\u01b0\u1ee3ng d\u1eef li\u1ec7u kh\u1ed5ng l\u1ed3 \u0111\u1ec3 \u201chu\u1ea5n luy\u1ec7n\u201d h\u1ec7 th\u1ed1ng.<\/p>\n<h3>S\u01a1 ch\u1ebf<\/h3>\n<p>Li\u00ean quan \u0111\u1ebfn vi\u1ec7c l\u00e0m s\u1ea1ch v\u00e0 t\u1ed5 ch\u1ee9c d\u1eef li\u1ec7u. \u0110i\u1ec1u n\u00e0y c\u00f3 th\u1ec3 bao g\u1ed3m gi\u1ea3m nhi\u1ec5u, chu\u1ea9n h\u00f3a v\u00e0 c\u00e1c k\u1ef9 thu\u1eadt kh\u00e1c \u0111\u1ec3 chu\u1ea9n b\u1ecb d\u1eef li\u1ec7u cho ph\u00e2n t\u00edch.<\/p>\n<h3>Khai th\u00e1c t\u00ednh n\u0103ng<\/h3>\n<p>B\u01b0\u1edbc n\u00e0y x\u00e1c \u0111\u1ecbnh c\u00e1c \u0111\u1eb7c \u0111i\u1ec3m ch\u00ednh ho\u1eb7c \u201c\u0111\u1eb7c \u0111i\u1ec3m\u201d c\u1ee7a m\u1ed9t \u0111\u1ed1i t\u01b0\u1ee3ng, ch\u1eb3ng h\u1ea1n nh\u01b0 c\u00e1c c\u1ea1nh, g\u00f3c, h\u1ecda ti\u1ebft v\u00e0 m\u00e0u s\u1eafc.<\/p>\n<h3>Ph\u00e2n lo\u1ea1i<\/h3>\n<p>Giai \u0111o\u1ea1n cu\u1ed1i c\u00f9ng li\u00ean quan \u0111\u1ebfn vi\u1ec7c g\u00e1n \u0111\u1ed1i t\u01b0\u1ee3ng v\u00e0o m\u1ed9t danh m\u1ee5c c\u1ee5 th\u1ec3 d\u1ef1a tr\u00ean c\u00e1c t\u00ednh n\u0103ng c\u1ee7a n\u00f3.<\/p>\n<h2>C\u1ea5u tr\u00fac b\u00ean trong c\u1ee7a nh\u1eadn d\u1ea1ng \u0111\u1ed1i t\u01b0\u1ee3ng: C\u00e1ch th\u1ee9c ho\u1ea1t \u0111\u1ed9ng c\u1ee7a nh\u1eadn d\u1ea1ng \u0111\u1ed1i t\u01b0\u1ee3ng<\/h2>\n<ol>\n<li><strong>Thu nh\u1eadn \u1ea3nh<\/strong>: H\u00ecnh \u1ea3nh \u0111\u01b0\u1ee3c ch\u1ee5p qua m\u00e1y \u1ea3nh ho\u1eb7c thi\u1ebft b\u1ecb h\u00ecnh \u1ea3nh kh\u00e1c.<\/li>\n<li><strong>S\u01a1 ch\u1ebf<\/strong>: H\u00ecnh \u1ea3nh \u0111\u01b0\u1ee3c chu\u1ea9n b\u1ecb \u0111\u1ec3 ph\u00e2n t\u00edch.<\/li>\n<li><strong>Khai th\u00e1c t\u00ednh n\u0103ng<\/strong>: C\u00e1c \u0111\u1eb7c \u0111i\u1ec3m ch\u00ednh \u0111\u01b0\u1ee3c x\u00e1c \u0111\u1ecbnh.<\/li>\n<li><strong>Ph\u00e2n lo\u1ea1i<\/strong>: \u0110\u1ed1i t\u01b0\u1ee3ng \u0111\u01b0\u1ee3c nh\u1eadn d\u1ea1ng v\u00e0 ph\u00e2n lo\u1ea1i.<\/li>\n<\/ol>\n<h2>Ph\u00e2n t\u00edch c\u00e1c t\u00ednh n\u0103ng ch\u00ednh c\u1ee7a nh\u1eadn d\u1ea1ng \u0111\u1ed1i t\u01b0\u1ee3ng<\/h2>\n<ul>\n<li><strong>S\u1ef1 ch\u00ednh x\u00e1c<\/strong>: C\u00e1c ph\u01b0\u01a1ng ph\u00e1p hi\u1ec7n \u0111\u1ea1i c\u00f3 th\u1ec3 \u0111\u1ea1t \u0111\u01b0\u1ee3c t\u1ef7 l\u1ec7 ch\u00ednh x\u00e1c cao.<\/li>\n<li><strong>X\u1eed l\u00fd th\u1eddi gian th\u1ef1c<\/strong>: C\u00f3 kh\u1ea3 n\u0103ng x\u1eed l\u00fd h\u00ecnh \u1ea3nh theo th\u1eddi gian th\u1ef1c.<\/li>\n<li><strong>Kh\u1ea3 n\u0103ng m\u1edf r\u1ed9ng<\/strong>: C\u00f3 th\u1ec3 \u00e1p d\u1ee5ng cho nhi\u1ec1u \u1ee9ng d\u1ee5ng kh\u00e1c nhau.<\/li>\n<li><strong>S\u1ef1 ph\u1ee5 thu\u1ed9c v\u00e0o d\u1eef li\u1ec7u<\/strong>: C\u1ea7n m\u1ed9t l\u01b0\u1ee3ng \u0111\u00e1ng k\u1ec3 d\u1eef li\u1ec7u \u0111\u01b0\u1ee3c d\u00e1n nh\u00e3n \u0111\u1ec3 hu\u1ea5n luy\u1ec7n.<\/li>\n<\/ul>\n<h2>C\u00e1c lo\u1ea1i nh\u1eadn d\u1ea1ng \u0111\u1ed1i t\u01b0\u1ee3ng<\/h2>\n<table>\n<thead>\n<tr>\n<th><strong>Ki\u1ec3u<\/strong><\/th>\n<th><strong>S\u1ef1 mi\u00eau t\u1ea3<\/strong><\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td>So kh\u1edbp m\u1eabu<\/td>\n<td>So s\u00e1nh c\u00e1c \u0111\u1ed1i t\u01b0\u1ee3ng v\u1edbi c\u00e1c m\u1eabu \u0111\u01b0\u1ee3c x\u00e1c \u0111\u1ecbnh tr\u01b0\u1edbc.<\/td>\n<\/tr>\n<tr>\n<td>So kh\u1edbp d\u1ef1a tr\u00ean t\u00ednh n\u0103ng<\/td>\n<td>Nh\u1eadn d\u1ea1ng c\u00e1c \u0111\u1ed1i t\u01b0\u1ee3ng d\u1ef1a tr\u00ean c\u00e1c t\u00ednh n\u0103ng \u0111\u01b0\u1ee3c tr\u00edch xu\u1ea5t.<\/td>\n<\/tr>\n<tr>\n<td>H\u1ecdc k\u0129 c\u00e0ng<\/td>\n<td>S\u1eed d\u1ee5ng m\u1ea1ng l\u01b0\u1edbi th\u1ea7n kinh \u0111\u1ec3 nh\u1eadn d\u1ea1ng.<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<h2>C\u00e1ch s\u1eed d\u1ee5ng t\u00ednh n\u0103ng nh\u1eadn d\u1ea1ng \u0111\u1ed1i t\u01b0\u1ee3ng, c\u00e1c v\u1ea5n \u0111\u1ec1 v\u00e0 gi\u1ea3i ph\u00e1p li\u00ean quan \u0111\u1ebfn vi\u1ec7c s\u1eed d\u1ee5ng<\/h2>\n<h3>C\u00f4ng d\u1ee5ng<\/h3>\n<ul>\n<li>H\u1ec7 th\u1ed1ng an ninh<\/li>\n<li>H\u00ecnh \u1ea3nh y t\u1ebf<\/li>\n<li>Ng\u01b0\u1eddi m\u00e1y<\/li>\n<li>Xe t\u1ef1 l\u00e1i<\/li>\n<\/ul>\n<h3>C\u00e1c v\u1ea5n \u0111\u1ec1<\/h3>\n<ul>\n<li>S\u1ef1 thay \u0111\u1ed5i v\u1ec1 h\u00ecnh th\u1ee9c \u0111\u1ed1i t\u01b0\u1ee3ng<\/li>\n<li>T\u1eafc ngh\u1ebdn<\/li>\n<li>C\u00e1c bi\u1ebfn th\u1ec3 c\u1ee7a thang \u00e2m<\/li>\n<\/ul>\n<h3>C\u00e1c gi\u1ea3i ph\u00e1p<\/h3>\n<ul>\n<li>Thu\u1eadt to\u00e1n c\u1ea3i ti\u1ebfn<\/li>\n<li>Thu th\u1eadp d\u1eef li\u1ec7u t\u1ed1t h\u01a1n<\/li>\n<li>K\u1ef9 thu\u1eadt ti\u1ec1n x\u1eed l\u00fd n\u00e2ng cao<\/li>\n<\/ul>\n<h2>C\u00e1c \u0111\u1eb7c \u0111i\u1ec3m ch\u00ednh v\u00e0 nh\u1eefng so s\u00e1nh kh\u00e1c v\u1edbi c\u00e1c thu\u1eadt ng\u1eef t\u01b0\u01a1ng t\u1ef1<\/h2>\n<table>\n<thead>\n<tr>\n<th><strong>Thu\u1eadt ng\u1eef<\/strong><\/th>\n<th><strong>S\u1ef1 mi\u00eau t\u1ea3<\/strong><\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td>Nh\u1eadn d\u1ea1ng \u0111\u1ed1i t\u01b0\u1ee3ng<\/td>\n<td>Nh\u1eadn d\u1ea1ng v\u00e0 ph\u00e2n lo\u1ea1i \u0111\u1ed3 v\u1eadt.<\/td>\n<\/tr>\n<tr>\n<td>Nh\u1eadn d\u1ea1ng h\u00ecnh \u1ea3nh<\/td>\n<td>Nh\u1eadn d\u1ea1ng to\u00e0n b\u1ed9 h\u00ecnh \u1ea3nh ho\u1eb7c c\u1ea3nh.<\/td>\n<\/tr>\n<tr>\n<td>Nh\u1eadn d\u1ea1ng khu\u00f4n m\u1eb7t<\/td>\n<td>Nh\u1eadn d\u1ea1ng t\u1eebng khu\u00f4n m\u1eb7t.<\/td>\n<\/tr>\n<tr>\n<td>Nh\u1eadn d\u1ea1ng m\u1eabu<\/td>\n<td>Nh\u1eadn bi\u1ebft c\u00e1c m\u00f4 h\u00ecnh v\u00e0 quy lu\u1eadt.<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<h2>Quan \u0111i\u1ec3m v\u00e0 c\u00f4ng ngh\u1ec7 c\u1ee7a t\u01b0\u01a1ng lai li\u00ean quan \u0111\u1ebfn nh\u1eadn d\u1ea1ng \u0111\u1ed1i t\u01b0\u1ee3ng<\/h2>\n<p>C\u00e1c c\u00f4ng ngh\u1ec7 trong t\u01b0\u01a1ng lai c\u00f3 th\u1ec3 bao g\u1ed3m c\u1ea3i thi\u1ec7n kh\u1ea3 n\u0103ng x\u1eed l\u00fd theo th\u1eddi gian th\u1ef1c, n\u00e2ng cao kh\u1ea3 n\u0103ng nh\u1eadn d\u1ea1ng \u0111\u1ed1i t\u01b0\u1ee3ng ba chi\u1ec1u, t\u00edch h\u1ee3p v\u1edbi th\u1ef1c t\u1ebf t\u0103ng c\u01b0\u1eddng v\u00e0 c\u00e1c c\u00e2n nh\u1eafc v\u1ec1 m\u1eb7t \u0111\u1ea1o \u0111\u1ee9c li\u00ean quan \u0111\u1ebfn quy\u1ec1n ri\u00eang t\u01b0 v\u00e0 th\u00e0nh ki\u1ebfn.<\/p>\n<h2>C\u00e1ch m\u00e1y ch\u1ee7 proxy c\u00f3 th\u1ec3 \u0111\u01b0\u1ee3c s\u1eed d\u1ee5ng ho\u1eb7c li\u00ean k\u1ebft v\u1edbi nh\u1eadn d\u1ea1ng \u0111\u1ed1i t\u01b0\u1ee3ng<\/h2>\n<p>C\u00e1c m\u00e1y ch\u1ee7 proxy gi\u1ed1ng nh\u01b0 c\u00e1c m\u00e1y ch\u1ee7 do OneProxy cung c\u1ea5p c\u00f3 th\u1ec3 \u0111\u00f3ng m\u1ed9t vai tr\u00f2 quan tr\u1ecdng trong vi\u1ec7c nh\u1eadn d\u1ea1ng \u0111\u1ed1i t\u01b0\u1ee3ng. Ch\u00fang cho ph\u00e9p thu th\u1eadp d\u1eef li\u1ec7u an to\u00e0n v\u00e0 \u1ea9n danh, \u0111i\u1ec1u n\u00e0y c\u00f3 th\u1ec3 c\u1ea7n thi\u1ebft cho vi\u1ec7c thu th\u1eadp d\u1eef li\u1ec7u \u0111\u00e0o t\u1ea1o. Ngo\u00e0i ra, m\u00e1y ch\u1ee7 proxy c\u00f3 th\u1ec3 gi\u00fap c\u00e2n b\u1eb1ng t\u1ea3i v\u00e0 \u0111\u1ea3m b\u1ea3o d\u1ecbch v\u1ee5 kh\u00f4ng b\u1ecb gi\u00e1n \u0111o\u1ea1n trong c\u00e1c \u1ee9ng d\u1ee5ng nh\u1eadn d\u1ea1ng \u0111\u1ed1i t\u01b0\u1ee3ng quy m\u00f4 l\u1edbn.<\/p>\n<h2>Li\u00ean k\u1ebft li\u00ean quan<\/h2>\n<ul>\n<li><a href=\"https:\/\/opencv.org\/\" target=\"_new\" rel=\"noopener nofollow\">OpenCV: Th\u01b0 vi\u1ec7n th\u1ecb gi\u00e1c m\u00e1y t\u00ednh m\u00e3 ngu\u1ed3n m\u1edf<\/a><\/li>\n<li><a href=\"https:\/\/www.tensorflow.org\/\" target=\"_new\" rel=\"noopener nofollow\">TensorFlow: Khung h\u1ecdc m\u00e1y m\u00e3 ngu\u1ed3n m\u1edf<\/a><\/li>\n<li><a href=\"https:\/\/oneproxy.pro\/vn\/\" target=\"_new\" rel=\"noopener\">OneProxy: D\u1ecbch v\u1ee5 proxy an to\u00e0n v\u00e0 \u0111\u00e1ng tin c\u1eady<\/a><\/li>\n<\/ul>\n<p>Vi\u1ec7c t\u00edch h\u1ee3p nh\u1eadn d\u1ea1ng \u0111\u1ed1i t\u01b0\u1ee3ng v\u1edbi c\u00e1c c\u00f4ng ngh\u1ec7 m\u1edbi n\u1ed5i kh\u00e1c h\u1ee9a h\u1eb9n m\u1ed9t t\u01b0\u01a1ng lai th\u00fa v\u1ecb. B\u1eb1ng c\u00e1ch hi\u1ec3u l\u1ecbch s\u1eed, \u1ee9ng d\u1ee5ng, ho\u1ea1t \u0111\u1ed9ng v\u00e0 tri\u1ec3n v\u1ecdng trong t\u01b0\u01a1ng lai c\u1ee7a n\u00f3, c\u00e1c doanh nghi\u1ec7p v\u00e0 c\u00e1 nh\u00e2n c\u00f3 th\u1ec3 t\u1eadn d\u1ee5ng c\u00f4ng c\u1ee5 m\u1ea1nh m\u1ebd n\u00e0y cho nhi\u1ec1u \u1ee9ng d\u1ee5ng, \u0111\u01b0\u1ee3c h\u1ed7 tr\u1ee3 b\u1edfi c\u00e1c d\u1ecbch v\u1ee5 nh\u01b0 OneProxy.<\/p>","protected":false},"featured_media":469046,"menu_order":0,"template":"","meta":{"_acf_changed":false,"content-type":"","inline_featured_image":false,"footnotes":""},"class_list":["post-478247","wiki","type-wiki","status-publish","has-post-thumbnail","hentry"],"acf":{"faq_title":"Frequently Asked Questions about <mark>Object Recognition<\/mark>","faq_items":[{"question":"What is Object Recognition?","answer":"<p>Object recognition is a process used in computer vision that enables machines to identify and categorize objects within images or videos. It is applied in various domains including robotics, security, healthcare, and autonomous vehicles.<\/p>"},{"question":"What are the stages involved in Object Recognition?","answer":"<p>Object recognition involves three main stages: preprocessing, where the data is cleaned and organized; feature extraction, where key characteristics of the object are identified; and classification, where the object is recognized and categorized.<\/p>"},{"question":"How did Object Recognition originate?","answer":"<p>Object recognition dates back to the early 1960s with researchers exploring the ability to mimic human perception using computers. The development has been continuous since then, evolving into a complex technology involving deep learning and neural networks.<\/p>"},{"question":"What are the types of Object Recognition?","answer":"<p>Three main types of Object Recognition include Template Matching, Feature-Based Matching, and Deep Learning. Template Matching compares objects to predefined templates, Feature-Based Matching recognizes objects based on extracted features, and Deep Learning utilizes neural networks.<\/p>"},{"question":"What are some common uses of Object Recognition?","answer":"<p>Object recognition is widely used in security systems, medical imaging, robotics, and autonomous vehicles. It serves various industries and fields, enhancing efficiency and accuracy.<\/p>"},{"question":"What problems might be encountered with Object Recognition, and how are they solved?","answer":"<p>Some challenges with object recognition include variability in object appearance, occlusion, and scale variations. Solutions include the development of improved algorithms, better data collection, and enhanced preprocessing techniques.<\/p>"},{"question":"How are proxy servers like OneProxy associated with Object Recognition?","answer":"<p>Proxy servers provided by OneProxy can enable secure and anonymous data collection, vital for gathering training data in object recognition. They can also help in balancing loads and ensuring uninterrupted service in large-scale applications.<\/p>"},{"question":"What are the future perspectives of Object Recognition?","answer":"<p>Future technologies related to object recognition may include improved real-time processing, enhanced recognition of three-dimensional objects, integration with augmented reality, and considerations related to privacy and bias.<\/p>"},{"question":"How does Object Recognition differ from Image Recognition, Facial Recognition, and Pattern Recognition?","answer":"<p>Object Recognition identifies and categorizes objects within images or videos. Image Recognition recognizes entire images or scenes, Facial Recognition recognizes individual faces, and Pattern Recognition recognizes patterns and regularities. Each has unique applications and methods.<\/p>"},{"question":"Where can I find more resources about Object Recognition?","answer":"<p>Resources like OpenCV, TensorFlow, and OneProxy provide in-depth information, tools, and services related to Object Recognition. Their respective websites offer extensive materials for further exploration.<\/p>"}]},"_links":{"self":[{"href":"https:\/\/oneproxy.pro\/vn\/wp-json\/wp\/v2\/wiki\/478247","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/oneproxy.pro\/vn\/wp-json\/wp\/v2\/wiki"}],"about":[{"href":"https:\/\/oneproxy.pro\/vn\/wp-json\/wp\/v2\/types\/wiki"}],"version-history":[{"count":0,"href":"https:\/\/oneproxy.pro\/vn\/wp-json\/wp\/v2\/wiki\/478247\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/oneproxy.pro\/vn\/wp-json\/wp\/v2\/media\/469046"}],"wp:attachment":[{"href":"https:\/\/oneproxy.pro\/vn\/wp-json\/wp\/v2\/media?parent=478247"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}