{"id":8542,"date":"2012-11-15T00:32:10","date_gmt":"2012-11-15T08:32:10","guid":{"rendered":"http:\/\/betaknowledge.tumblr.com\/post\/35765441795"},"modified":"2017-08-18T17:57:52","modified_gmt":"2017-08-18T17:57:52","slug":"what-makes-paris-look-like-parisgiven-a-large","status":"publish","type":"post","link":"https:\/\/blog.nearfuturelaboratory.com\/2012\/11\/15\/what-makes-paris-look-like-parisgiven-a-large\/","title":{"rendered":"\u201cWhat makes Paris look like Paris\u201d\n\nGiven a large\u2026"},"content":{"rendered":"<img src=\"http:\/\/25.media.tumblr.com\/tumblr_mdit1mScy01qgczcwo1_500.jpg\"\/><br\/><br\/><p>\u201cWhat makes Paris look like Paris\u201d<\/p>\n<blockquote>\n<p><em>Given a large repository of geotagged imagery, we seek to automatically find visual elements, e.g. windows, balconies, and street signs, that are most distinctive for a certain geo-spatial area, for example the city of Paris. [\u2026] To address these issues, we propose to use a discriminative clustering approach able to take into account the weak geographic supervision. We show that geographically representative image elements can be discovered automatically from Google Street View imagery in a discriminative manner.<\/em><\/p>\n<\/blockquote><div class=\"feedflare\">\n<a href=\"http:\/\/feeds.feedburner.com\/~ff\/NicolasNova?a=Nb6r7KowvAk:FtjyqQf6zFk:yIl2AUoC8zA\"><img src=\"http:\/\/feeds.feedburner.com\/~ff\/NicolasNova?d=yIl2AUoC8zA\" border=\"0\"><\/img><\/a> <a href=\"http:\/\/feeds.feedburner.com\/~ff\/NicolasNova?a=Nb6r7KowvAk:FtjyqQf6zFk:qj6IDK7rITs\"><img src=\"http:\/\/feeds.feedburner.com\/~ff\/NicolasNova?d=qj6IDK7rITs\" border=\"0\"><\/img><\/a> <a href=\"http:\/\/feeds.feedburner.com\/~ff\/NicolasNova?a=Nb6r7KowvAk:FtjyqQf6zFk:F7zBnMyn0Lo\"><img src=\"http:\/\/feeds.feedburner.com\/~ff\/NicolasNova?i=Nb6r7KowvAk:FtjyqQf6zFk:F7zBnMyn0Lo\" border=\"0\"><\/img><\/a>\n<\/div><img src=\"http:\/\/feeds.feedburner.com\/~r\/NicolasNova\/~4\/Nb6r7KowvAk\" height=\"1\" width=\"1\"\/>","protected":false},"excerpt":{"rendered":"<p>\u201cWhat makes Paris look like Paris\u201d<\/p>\n<p>Given a large repository of geotagged imagery, we seek to automatically find visual elements, e.g. windows, balconies, and street signs, that are most distinctive for a certain geo-spatial area, for example the c&#8230;<\/p>\n","protected":false},"author":5,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":[],"categories":[169],"tags":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v14.9 - 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