{"id":477976,"date":"2023-08-09T09:23:20","date_gmt":"2023-08-09T09:23:20","guid":{"rendered":""},"modified":"2023-09-05T11:15:49","modified_gmt":"2023-09-05T11:15:49","slug":"mean-shift-clustering","status":"publish","type":"wiki","link":"https:\/\/oneproxy.pro\/vn\/wiki\/mean-shift-clustering\/","title":{"rendered":"Ph\u00e2n c\u1ee5m d\u1ecbch chuy\u1ec3n trung b\u00ecnh"},"content":{"rendered":"<p>Ph\u00e2n c\u1ee5m d\u1ecbch chuy\u1ec3n trung b\u00ecnh l\u00e0 m\u1ed9t k\u1ef9 thu\u1eadt ph\u00e2n c\u1ee5m phi tham s\u1ed1 linh ho\u1ea1t v\u00e0 m\u1ea1nh m\u1ebd \u0111\u01b0\u1ee3c s\u1eed d\u1ee5ng \u0111\u1ec3 x\u00e1c \u0111\u1ecbnh c\u00e1c m\u1eabu v\u00e0 c\u1ea5u tr\u00fac trong m\u1ed9t t\u1eadp d\u1eef li\u1ec7u. Kh\u00f4ng gi\u1ed1ng nh\u01b0 c\u00e1c thu\u1eadt to\u00e1n ph\u00e2n c\u1ee5m kh\u00e1c, d\u1ecbch chuy\u1ec3n trung b\u00ecnh kh\u00f4ng c\u00f3 b\u1ea5t k\u1ef3 h\u00ecnh d\u1ea1ng n\u00e0o \u0111\u01b0\u1ee3c x\u00e1c \u0111\u1ecbnh tr\u01b0\u1edbc cho c\u00e1c c\u1ee5m d\u1eef li\u1ec7u v\u00e0 c\u00f3 th\u1ec3 th\u00edch \u1ee9ng v\u1edbi c\u00e1c m\u1eadt \u0111\u1ed9 kh\u00e1c nhau. Ph\u01b0\u01a1ng ph\u00e1p n\u00e0y d\u1ef1a tr\u00ean h\u00e0m m\u1eadt \u0111\u1ed9 x\u00e1c su\u1ea5t c\u01a1 b\u1ea3n c\u1ee7a d\u1eef li\u1ec7u, l\u00e0m cho n\u00f3 ph\u00f9 h\u1ee3p v\u1edbi nhi\u1ec1u \u1ee9ng d\u1ee5ng kh\u00e1c nhau, bao g\u1ed3m ph\u00e2n \u0111o\u1ea1n h\u00ecnh \u1ea3nh, theo d\u00f5i \u0111\u1ed1i t\u01b0\u1ee3ng v\u00e0 ph\u00e2n t\u00edch d\u1eef li\u1ec7u.<\/p>\n<h2>L\u1ecbch s\u1eed ngu\u1ed3n g\u1ed1c c\u1ee7a ph\u00e2n c\u1ee5m d\u1ecbch chuy\u1ec3n trung b\u00ecnh v\u00e0 s\u1ef1 \u0111\u1ec1 c\u1eadp \u0111\u1ea7u ti\u00ean v\u1ec1 n\u00f3<\/h2>\n<p>Thu\u1eadt to\u00e1n d\u1ecbch chuy\u1ec3n trung b\u00ecnh c\u00f3 ngu\u1ed3n g\u1ed1c t\u1eeb l\u0129nh v\u1ef1c th\u1ecb gi\u00e1c m\u00e1y t\u00ednh v\u00e0 \u0111\u01b0\u1ee3c Fukunaga v\u00e0 Hostetler gi\u1edbi thi\u1ec7u l\u1ea7n \u0111\u1ea7u ti\u00ean v\u00e0o n\u0103m 1975. Ban \u0111\u1ea7u n\u00f3 \u0111\u01b0\u1ee3c s\u1eed d\u1ee5ng \u0111\u1ec3 ph\u00e2n t\u00edch c\u1ee5m trong c\u00e1c nhi\u1ec7m v\u1ee5 th\u1ecb gi\u00e1c m\u00e1y t\u00ednh, nh\u01b0ng kh\u1ea3 n\u0103ng \u1ee9ng d\u1ee5ng c\u1ee7a n\u00f3 nhanh ch\u00f3ng lan r\u1ed9ng sang nhi\u1ec1u l\u0129nh v\u1ef1c kh\u00e1c nhau nh\u01b0 x\u1eed l\u00fd h\u00ecnh \u1ea3nh, nh\u1eadn d\u1ea1ng m\u1eabu v\u00e0 h\u1ecdc m\u00e1y.<\/p>\n<h2>Th\u00f4ng tin chi ti\u1ebft v\u1ec1 ph\u00e2n c\u1ee5m d\u1ecbch chuy\u1ec3n trung b\u00ecnh: M\u1edf r\u1ed9ng ch\u1ee7 \u0111\u1ec1<\/h2>\n<p>Ph\u00e2n c\u1ee5m d\u1ecbch chuy\u1ec3n trung b\u00ecnh ho\u1ea1t \u0111\u1ed9ng b\u1eb1ng c\u00e1ch d\u1ecbch chuy\u1ec3n l\u1eb7p \u0111i l\u1eb7p l\u1ea1i c\u00e1c \u0111i\u1ec3m d\u1eef li\u1ec7u sang ch\u1ebf \u0111\u1ed9 c\u1ee7a h\u00e0m m\u1eadt \u0111\u1ed9 c\u1ee5c b\u1ed9 t\u01b0\u01a1ng \u1ee9ng c\u1ee7a ch\u00fang. \u0110\u00e2y l\u00e0 c\u00e1ch thu\u1eadt to\u00e1n m\u1edf ra:<\/p>\n<ol>\n<li><strong>L\u1ef1a ch\u1ecdn h\u1ea1t nh\u00e2n<\/strong>: M\u1ed9t h\u1ea1t nh\u00e2n (th\u01b0\u1eddng l\u00e0 Gaussian) \u0111\u01b0\u1ee3c \u0111\u1eb7t t\u1ea1i m\u1ed7i \u0111i\u1ec3m d\u1eef li\u1ec7u.<\/li>\n<li><strong>D\u1ecbch chuy\u1ec3n<\/strong>: M\u1ed7i \u0111i\u1ec3m d\u1eef li\u1ec7u \u0111\u01b0\u1ee3c d\u1ecbch chuy\u1ec3n v\u1ec1 ph\u00eda gi\u00e1 tr\u1ecb trung b\u00ecnh c\u1ee7a c\u00e1c \u0111i\u1ec3m trong nh\u00e2n c\u1ee7a n\u00f3.<\/li>\n<li><strong>h\u1ed9i t\u1ee5<\/strong>: S\u1ef1 d\u1ecbch chuy\u1ec3n ti\u1ebfp t\u1ee5c l\u1eb7p \u0111i l\u1eb7p l\u1ea1i cho \u0111\u1ebfn khi h\u1ed9i t\u1ee5, t\u1ee9c l\u00e0 s\u1ef1 d\u1ecbch chuy\u1ec3n n\u1eb1m d\u01b0\u1edbi ng\u01b0\u1ee1ng \u0111\u01b0\u1ee3c x\u00e1c \u0111\u1ecbnh tr\u01b0\u1edbc.<\/li>\n<li><strong>h\u00ecnh th\u00e0nh c\u1ee5m<\/strong>: C\u00e1c \u0111i\u1ec3m d\u1eef li\u1ec7u h\u1ed9i t\u1ee5 v\u1ec1 c\u00f9ng m\u1ed9t ch\u1ebf \u0111\u1ed9 \u0111\u01b0\u1ee3c nh\u00f3m l\u1ea1i v\u1edbi nhau th\u00e0nh m\u1ed9t c\u1ee5m.<\/li>\n<\/ol>\n<h2>C\u1ea5u tr\u00fac b\u00ean trong c\u1ee7a ph\u00e2n c\u1ee5m d\u1ecbch chuy\u1ec3n trung b\u00ecnh: C\u00e1ch th\u1ee9c ho\u1ea1t \u0111\u1ed9ng<\/h2>\n<p>C\u1ed1t l\u00f5i c\u1ee7a ph\u00e2n c\u1ee5m d\u1ecbch chuy\u1ec3n trung b\u00ecnh l\u00e0 quy tr\u00ecnh d\u1ecbch chuy\u1ec3n trong \u0111\u00f3 m\u1ed7i \u0111i\u1ec3m d\u1eef li\u1ec7u di chuy\u1ec3n v\u1ec1 ph\u00eda v\u00f9ng d\u00e0y \u0111\u1eb7c nh\u1ea5t trong v\u00f9ng l\u00e2n c\u1eadn c\u1ee7a n\u00f3. C\u00e1c th\u00e0nh ph\u1ea7n ch\u00ednh bao g\u1ed3m:<\/p>\n<ul>\n<li><strong>B\u0103ng th\u00f4ng<\/strong>: M\u1ed9t tham s\u1ed1 quan tr\u1ecdng x\u00e1c \u0111\u1ecbnh k\u00edch th\u01b0\u1edbc c\u1ee7a h\u1ea1t nh\u00e2n v\u00e0 do \u0111\u00f3 \u1ea3nh h\u01b0\u1edfng \u0111\u1ebfn \u0111\u1ed9 chi ti\u1ebft c\u1ee7a ph\u00e2n c\u1ee5m.<\/li>\n<li><strong>Ch\u1ee9c n\u0103ng h\u1ea1t nh\u00e2n<\/strong>: H\u00e0m kernel x\u00e1c \u0111\u1ecbnh h\u00ecnh d\u1ea1ng v\u00e0 k\u00edch th\u01b0\u1edbc c\u1ee7a c\u1eeda s\u1ed5 \u0111\u01b0\u1ee3c s\u1eed d\u1ee5ng \u0111\u1ec3 t\u00ednh gi\u00e1 tr\u1ecb trung b\u00ecnh.<\/li>\n<li><strong>\u0110\u01b0\u1eddng d\u1eabn t\u00ecm ki\u1ebfm<\/strong>: \u0110\u01b0\u1eddng \u0111i theo t\u1eebng \u0111i\u1ec3m d\u1eef li\u1ec7u cho \u0111\u1ebfn khi h\u1ed9i t\u1ee5.<\/li>\n<\/ul>\n<h2>Ph\u00e2n t\u00edch c\u00e1c \u0111\u1eb7c \u0111i\u1ec3m ch\u00ednh c\u1ee7a ph\u00e2n c\u1ee5m d\u1ecbch chuy\u1ec3n trung b\u00ecnh<\/h2>\n<ul>\n<li><strong>\u0110\u1ed9 b\u1ec1n<\/strong>: N\u00f3 kh\u00f4ng \u0111\u01b0a ra gi\u1ea3 \u0111\u1ecbnh v\u1ec1 h\u00ecnh d\u1ea1ng c\u1ee7a c\u1ee5m.<\/li>\n<li><strong>Uy\u1ec3n chuy\u1ec3n<\/strong>: Th\u00edch \u1ee9ng v\u1edbi c\u00e1c lo\u1ea1i d\u1eef li\u1ec7u v\u00e0 quy m\u00f4 kh\u00e1c nhau.<\/li>\n<li><strong>T\u00ednh to\u00e1n chuy\u00ean s\u00e2u<\/strong>: C\u00f3 th\u1ec3 ch\u1eadm \u0111\u1ed1i v\u1edbi c\u00e1c t\u1eadp d\u1eef li\u1ec7u l\u1edbn.<\/li>\n<li><strong>\u0110\u1ed9 nh\u1ea1y tham s\u1ed1<\/strong>: Hi\u1ec7u su\u1ea5t ph\u1ee5 thu\u1ed9c v\u00e0o b\u0103ng th\u00f4ng \u0111\u01b0\u1ee3c ch\u1ecdn.<\/li>\n<\/ul>\n<h2>C\u00e1c lo\u1ea1i ph\u00e2n c\u1ee5m d\u1ecbch chuy\u1ec3n trung b\u00ecnh<\/h2>\n<p>C\u00f3 nhi\u1ec1u phi\u00ean b\u1ea3n kh\u00e1c nhau c\u1ee7a ph\u00e2n c\u1ee5m d\u1ecbch chuy\u1ec3n trung b\u00ecnh, ch\u1ee7 y\u1ebfu kh\u00e1c nhau v\u1ec1 ch\u1ee9c n\u0103ng kernel v\u00e0 k\u1ef9 thu\u1eadt t\u1ed1i \u01b0u h\u00f3a.<\/p>\n<table>\n<thead>\n<tr>\n<th>Ki\u1ec3u<\/th>\n<th>h\u1ea1t nh\u00e2n<\/th>\n<th>\u1ee8ng d\u1ee5ng<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td>\u0110\u1ed9 d\u1ecbch chuy\u1ec3n trung b\u00ecnh chu\u1ea9n<\/td>\n<td>Gaussian<\/td>\n<td>Ph\u00e2n c\u1ee5m chung<\/td>\n<\/tr>\n<tr>\n<td>D\u1ecbch chuy\u1ec3n trung b\u00ecnh th\u00edch \u1ee9ng<\/td>\n<td>Bi\u1ebfn \u0111\u1ed5i<\/td>\n<td>Ph\u00e2n \u0111o\u1ea1n h\u00ecnh \u1ea3nh<\/td>\n<\/tr>\n<tr>\n<td>D\u1ecbch chuy\u1ec3n trung b\u00ecnh nhanh<\/td>\n<td>T\u1ed1i \u01b0u h\u00f3a<\/td>\n<td>X\u1eed l\u00fd th\u1eddi gian th\u1ef1c<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<h2>C\u00e1c c\u00e1ch s\u1eed d\u1ee5ng Ph\u00e2n c\u1ee5m d\u1ecbch chuy\u1ec3n trung b\u00ecnh, c\u00e1c v\u1ea5n \u0111\u1ec1 v\u00e0 gi\u1ea3i ph\u00e1p c\u1ee7a ch\u00fang<\/h2>\n<ul>\n<li><strong>C\u00f4ng d\u1ee5ng<\/strong>: Ph\u00e2n \u0111o\u1ea1n h\u00ecnh \u1ea3nh, theo d\u00f5i video, ph\u00e2n t\u00edch d\u1eef li\u1ec7u kh\u00f4ng gian.<\/li>\n<li><strong>C\u00e1c v\u1ea5n \u0111\u1ec1<\/strong>: L\u1ef1a ch\u1ecdn b\u0103ng th\u00f4ng, c\u00e1c v\u1ea5n \u0111\u1ec1 v\u1ec1 kh\u1ea3 n\u0103ng m\u1edf r\u1ed9ng, h\u1ed9i t\u1ee5 \u0111\u1ebfn c\u1ef1c \u0111\u1ea1i c\u1ee5c b\u1ed9.<\/li>\n<li><strong>C\u00e1c gi\u1ea3i ph\u00e1p<\/strong>: L\u1ef1a ch\u1ecdn b\u0103ng th\u00f4ng th\u00edch \u1ee9ng, x\u1eed l\u00fd song song, thu\u1eadt to\u00e1n lai.<\/li>\n<\/ul>\n<h2>C\u00e1c \u0111\u1eb7c \u0111i\u1ec3m ch\u00ednh v\u00e0 so s\u00e1nh kh\u00e1c v\u1edbi c\u00e1c ph\u01b0\u01a1ng ph\u00e1p t\u01b0\u01a1ng t\u1ef1<\/h2>\n<p>So s\u00e1nh ph\u00e2n c\u1ee5m d\u1ecbch chuy\u1ec3n trung b\u00ecnh v\u1edbi c\u00e1c ph\u01b0\u01a1ng ph\u00e1p ph\u00e2n c\u1ee5m kh\u00e1c:<\/p>\n<table>\n<thead>\n<tr>\n<th>Ph\u01b0\u01a1ng ph\u00e1p<\/th>\n<th>H\u00ecnh d\u1ea1ng c\u1ee7a c\u1ee5m<\/th>\n<th>\u0110\u1ed9 nh\u1ea1y v\u1edbi c\u00e1c th\u00f4ng s\u1ed1<\/th>\n<th>Kh\u1ea3 n\u0103ng m\u1edf r\u1ed9ng<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td>S\u1ef1 thay \u0111\u1ed5i trung b\u00ecnh<\/td>\n<td>Linh ho\u1ea1t<\/td>\n<td>Cao<\/td>\n<td>V\u1eeba ph\u1ea3i<\/td>\n<\/tr>\n<tr>\n<td>K-ngh\u0129a<\/td>\n<td>h\u00ecnh c\u1ea7u<\/td>\n<td>V\u1eeba ph\u1ea3i<\/td>\n<td>Cao<\/td>\n<\/tr>\n<tr>\n<td>DBSCAN<\/td>\n<td>B\u1ea5t k\u1ef3<\/td>\n<td>Th\u1ea5p<\/td>\n<td>V\u1eeba ph\u1ea3i<\/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 ph\u00e2n c\u1ee5m d\u1ecbch chuy\u1ec3n trung b\u00ecnh<\/h2>\n<p>S\u1ef1 ph\u00e1t tri\u1ec3n trong t\u01b0\u01a1ng lai c\u00f3 th\u1ec3 t\u1eadp trung v\u00e0o:<\/p>\n<ul>\n<li>N\u00e2ng cao hi\u1ec7u qu\u1ea3 t\u00ednh to\u00e1n.<\/li>\n<li>K\u1ebft h\u1ee3p h\u1ecdc s\u00e2u \u0111\u1ec3 l\u1ef1a ch\u1ecdn b\u0103ng th\u00f4ng t\u1ef1 \u0111\u1ed9ng.<\/li>\n<li>T\u00edch h\u1ee3p v\u1edbi c\u00e1c thu\u1eadt to\u00e1n kh\u00e1c cho gi\u1ea3i ph\u00e1p lai.<\/li>\n<\/ul>\n<h2>C\u00e1ch s\u1eed d\u1ee5ng ho\u1eb7c li\u00ean k\u1ebft m\u00e1y ch\u1ee7 proxy v\u1edbi ph\u00e2n c\u1ee5m d\u1ecbch chuy\u1ec3n trung b\u00ecnh<\/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\u01b0\u1ee3c s\u1eed d\u1ee5ng \u0111\u1ec3 h\u1ed7 tr\u1ee3 vi\u1ec7c thu th\u1eadp d\u1eef li\u1ec7u cho vi\u1ec7c ph\u00e2n t\u00edch ph\u00e2n c\u1ee5m. B\u1eb1ng c\u00e1ch s\u1eed d\u1ee5ng proxy, d\u1eef li\u1ec7u quy m\u00f4 l\u1edbn c\u00f3 th\u1ec3 \u0111\u01b0\u1ee3c l\u1ea5y t\u1eeb nhi\u1ec1u ngu\u1ed3n kh\u00e1c nhau m\u00e0 kh\u00f4ng b\u1ecb h\u1ea1n ch\u1ebf IP, cho ph\u00e9p ph\u00e2n t\u00edch to\u00e0n di\u1ec7n h\u01a1n b\u1eb1ng c\u00e1ch s\u1eed d\u1ee5ng ph\u00e2n c\u1ee5m d\u1ecbch chuy\u1ec3n trung b\u00ecnh.<\/p>\n<h2>Li\u00ean k\u1ebft li\u00ean quan<\/h2>\n<ul>\n<li><a href=\"https:\/\/example.com\/original-paper\" target=\"_new\" rel=\"noopener nofollow\">B\u00e0i vi\u1ebft g\u1ed1c c\u1ee7a Fukunaga v\u00e0 Hostetler<\/a><\/li>\n<li><a href=\"https:\/\/oneproxy.pro\/vn\/\" target=\"_new\" rel=\"noopener\">D\u1ecbch v\u1ee5 proxy c\u1ee7a OneProxy<\/a><\/li>\n<li><a href=\"https:\/\/example.com\/tutorial\" target=\"_new\" rel=\"noopener nofollow\">Gi\u1edbi thi\u1ec7u v\u1ec1 ph\u00e2n c\u1ee5m d\u1ecbch chuy\u1ec3n trung b\u00ecnh<\/a><\/li>\n<li><a href=\"https:\/\/example.com\/opencv\" target=\"_new\" rel=\"noopener nofollow\">S\u1ef1 thay \u0111\u1ed5i trung b\u00ecnh trong OpenCV<\/a><\/li>\n<li><a href=\"https:\/\/example.com\/advances\" target=\"_new\" rel=\"noopener nofollow\">Nh\u1eefng ti\u1ebfn b\u1ed9 g\u1ea7n \u0111\u00e2y trong s\u1ef1 d\u1ecbch chuy\u1ec3n trung b\u00ecnh<\/a><\/li>\n<\/ul>","protected":false},"featured_media":468881,"menu_order":0,"template":"","meta":{"_acf_changed":false,"content-type":"","inline_featured_image":false,"footnotes":""},"class_list":["post-477976","wiki","type-wiki","status-publish","has-post-thumbnail","hentry"],"acf":{"faq_title":"Frequently Asked Questions about <mark>Mean Shift Clustering<\/mark>","faq_items":[{"question":"What is Mean Shift Clustering?","answer":"<p>Mean Shift Clustering is a non-parametric clustering technique that identifies patterns within a data set without assuming any predefined shape for the clusters. It iteratively shifts data points towards dense regions, grouping them into clusters.<\/p>"},{"question":"What was the first mention of Mean Shift Clustering?","answer":"<p>Mean Shift Clustering was first introduced by Fukunaga and Hostetler in 1975, originally used for cluster analysis in computer vision tasks.<\/p>"},{"question":"How does Mean Shift Clustering work?","answer":"<p>Mean Shift Clustering works by placing a kernel at each data point and shifting these points towards the mean of their local region. This shifting continues until convergence, and data points converging to the same mode are grouped into a cluster.<\/p>"},{"question":"What are the key features of Mean Shift Clustering?","answer":"<p>The key features of Mean Shift Clustering include its robustness to different shapes of clusters, flexibility in handling various types of data, computational intensity, and sensitivity to the choice of the bandwidth parameter.<\/p>"},{"question":"What types of Mean Shift Clustering exist?","answer":"<p>Different types of Mean Shift Clustering exist, primarily differing in kernel functions and optimization techniques. Some examples include Standard Mean Shift with Gaussian kernel, Adaptive Mean Shift with variable kernel, and Fast Mean Shift with optimized techniques.<\/p>"},{"question":"What are the main applications and problems related to Mean Shift Clustering?","answer":"<p>Mean Shift Clustering is used in image segmentation, video tracking, and spatial data analysis. Problems may arise from the choice of bandwidth, scalability issues, and convergence to local maxima. Solutions include adaptive bandwidth selection, parallel processing, and hybrid algorithms.<\/p>"},{"question":"How does Mean Shift Clustering compare to other clustering methods like K-Means and DBSCAN?","answer":"<p>Mean Shift allows flexible shapes for clusters and is highly sensitive to parameter choices, with moderate scalability. In contrast, K-Means assumes spherical clusters and has high scalability, while DBSCAN allows arbitrary shapes with low sensitivity to parameters.<\/p>"},{"question":"What are the future perspectives and technologies related to Mean Shift Clustering?","answer":"<p>Future developments may include enhancing computational efficiency, incorporating deep learning for automated bandwidth selection, and integrating with other algorithms for hybrid solutions.<\/p>"},{"question":"How can proxy servers like OneProxy be associated with Mean Shift Clustering?","answer":"<p>Proxy servers from OneProxy can be used to facilitate data collection for clustering analysis. By using proxies, large-scale data can be gathered from various sources without IP restrictions, enabling more robust and comprehensive analysis using Mean Shift Clustering.<\/p>"}]},"_links":{"self":[{"href":"https:\/\/oneproxy.pro\/vn\/wp-json\/wp\/v2\/wiki\/477976","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\/477976\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/oneproxy.pro\/vn\/wp-json\/wp\/v2\/media\/468881"}],"wp:attachment":[{"href":"https:\/\/oneproxy.pro\/vn\/wp-json\/wp\/v2\/media?parent=477976"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}