{"id":201241,"date":"2024-12-11T00:40:03","date_gmt":"2024-12-11T06:40:03","guid":{"rendered":"https:\/\/lifeboat.com\/blog\/2024\/12\/multi-label-classification-in-ai-a-new-path-for-object-recognition"},"modified":"2024-12-11T00:40:03","modified_gmt":"2024-12-11T06:40:03","slug":"multi-label-classification-in-ai-a-new-path-for-object-recognition","status":"publish","type":"post","link":"https:\/\/lifeboat.com\/blog\/2024\/12\/multi-label-classification-in-ai-a-new-path-for-object-recognition","title":{"rendered":"Multi-label classification in AI: A new path for object recognition"},"content":{"rendered":"<p><a class=\"aligncenter blog-photo\" href=\"https:\/\/lifeboat.com\/blog.images\/multi-label-classification-in-ai-a-new-path-for-object-recognition2.jpg\"><\/a><\/p>\n<p>Image classification is one of AI\u2019s most common tasks, where a system is required to recognize an object from a given image. Yet real life requires us to recognize not a single standalone object but rather multiple objects appearing together in a given image.<\/p>\n<p>This reality raises the question: what is the best strategy to tackle multi-object <a href=\"https:\/\/techxplore.com\/tags\/classification\/\" rel=\"tag\" class=\"\">classification<\/a>? The common approach is to detect each object individually and then classify them. But new research challenges this customary approach to multi-object classification tasks.<\/p>\n<p>In an article published today in <a href=\"https:\/\/www.sciencedirect.com\/science\/article\/pii\/S0378437124008057\" target=\"_blank\"><i><i>Physica A<\/i>: Statistical Mechanics and its Applications<\/i><\/a>, researchers from Bar-Ilan University in Israel show how classifying objects together, through a process known as Multi-Label Classification (MLC), can surpass the common detection-based classification.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Image classification is one of AI\u2019s most common tasks, where a system is required to recognize an object from a given image. Yet real life requires us to recognize not a single standalone object but rather multiple objects appearing together in a given image. This reality raises the question: what is the best strategy to [\u2026]<\/p>\n","protected":false},"author":662,"featured_media":0,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[6],"tags":[],"class_list":["post-201241","post","type-post","status-publish","format-standard","hentry","category-robotics-ai"],"_links":{"self":[{"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/posts\/201241","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/users\/662"}],"replies":[{"embeddable":true,"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/comments?post=201241"}],"version-history":[{"count":0,"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/posts\/201241\/revisions"}],"wp:attachment":[{"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/media?parent=201241"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/categories?post=201241"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/tags?post=201241"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}