{"id":37004,"date":"2019-10-31T22:15:15","date_gmt":"2019-10-31T19:15:15","guid":{"rendered":"https:\/\/prohoster.info\/blog\/nejroset-beeline-ai-poisk-lyudej-pomozhet-najti-propavshih\/"},"modified":"2019-10-31T22:15:15","modified_gmt":"2019-10-31T19:15:15","slug":"nejroset-beeline-ai-poisk-lyudej-pomozhet-najti-propavshih","status":"publish","type":"post","link":"https:\/\/prohoster.info\/en\/blog\/news\/nejroset-beeline-ai-poisk-lyudej-pomozhet-najti-propavshih","title":{"rendered":"The neural network \"Beeline AI \u2014 People Search\" will help find missing persons","gt_translate_keys":[{"key":"rendered","format":"text"}]},"content":{"rendered":"

\u00abBeeline\u00bb has developed a specialized neural network to assist in finding missing persons: the platform is called \u00abBeeline AI \u2014 People Search\u00bb.<\/p>\n

This solution is designed to simplify the work of the search and rescue team \u00abLisa Alert<\/a><\/noindex>\u00bb. Since 2018, this team has been using unmanned aerial vehicles for search operations in forests and industrial areas of cities. However, analyzing images from drone cameras requires a large number of volunteers, which takes a significant amount of time.<\/p>\n

\"The<\/p>\n

The neural network \u00abBeeline AI \u2014 People Search\u00bb aims to automate the photo processing workflow. It is claimed that specialized algorithms reduce the time spent on viewing and sorting the obtained images by two and a half times.<\/p>\n

The platform utilizes convolutional neural network technology, which enhances the efficiency of machine vision tools. The neural network was trained on real image datasets. Tests showed that the model's accuracy on test images approaches 98%.<\/p>\n

<\/center><\/p>\n

The primary task of \u00abBeeline AI \u2014 People Search\u00bb is to filter out \u00abempty\u00bb and uninformative photographs that clearly do not contain a person or any clues indicating that a person was present. This allows the analysis team to focus immediately on potentially useful images.<\/p>\n

\"The<\/p>\n

The system can adapt to various conditions. It accurately identifies objects from heights of 30\u201340 meters as well as from a flight altitude of 100 meters. Additionally, the neural network can process images with a high level of visual \u00abnoise\u00bb \u2014 trees, natural landscapes, twilight, etc.<\/p>\n

\u00abPotentially, the neural network is capable of locating people and objects in all search areas, such as forests, swamps, fields, and cities, regardless of the season and the clothing of the person, as the algorithm is designed to operate year-round and can potentially recognize non-standard body positions in space, such as sitting, lying down, or a person partially concealed by foliage\u00bb, notes \u00abBeeline\u00bb. <\/p>\n

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Source: 3dnews.ru<\/a><\/p>","protected":false,"gt_translate_keys":[{"key":"rendered","format":"html"}]},"excerpt":{"rendered":"

«\u0411\u0438\u043b\u0430\u0439\u043d» \u0440\u0430\u0437\u0440\u0430\u0431\u043e\u0442\u0430\u043b \u0441\u043f\u0435\u0446\u0438\u0430\u043b\u0438\u0437\u0438\u0440\u043e\u0432\u0430\u043d\u043d\u0443\u044e \u043d\u0435\u0439\u0440\u043e\u043d\u043d\u0443\u044e \u0441\u0435\u0442\u044c, \u043a\u043e\u0442\u043e\u0440\u0430\u044f \u043f\u043e\u043c\u043e\u0436\u0435\u0442 \u0432 \u043f\u043e\u0438\u0441\u043a\u0435 \u043f\u0440\u043e\u043f\u0430\u0432\u0448\u0438\u0445: \u043f\u043b\u0430\u0442\u0444\u043e\u0440\u043c\u0430 \u043f\u043e\u043b\u0443\u0447\u0438\u043b\u0430 \u043d\u0430\u0437\u0432\u0430\u043d\u0438\u0435 «Beeline AI — \u041f\u043e\u0438\u0441\u043a \u043b\u044e\u0434\u0435\u0439». \u0420\u0435\u0448\u0435\u043d\u0438\u0435 \u043f\u0440\u0438\u0437\u0432\u0430\u043d\u043e \u0443\u043f\u0440\u043e\u0441\u0442\u0438\u0442\u044c \u0440\u0430\u0431\u043e\u0442\u0443 \u043f\u043e\u0438\u0441\u043a\u043e\u0432\u043e-\u0441\u043f\u0430\u0441\u0430\u0442\u0435\u043b\u044c\u043d\u043e\u0433\u043e \u043e\u0442\u0440\u044f\u0434\u0430 «\u041b\u0438\u0437\u0430 \u0410\u043b\u0435\u0440\u0442». \u0421 2018 \u0433\u043e\u0434\u0430 \u044d\u0442\u0430 \u043a\u043e\u043c\u0430\u043d\u0434\u0430 \u043f\u0440\u0438\u043c\u0435\u043d\u044f\u0435\u0442 \u0431\u0435\u0441\u043f\u0438\u043b\u043e\u0442\u043d\u044b\u0435 \u043b\u0435\u0442\u0430\u0442\u0435\u043b\u044c\u043d\u044b\u0435 \u0430\u043f\u043f\u0430\u0440\u0430\u0442\u044b \u0434\u043b\u044f \u043f\u043e\u0438\u0441\u043a\u043e\u0432\u044b\u0445 \u043e\u043f\u0435\u0440\u0430\u0446\u0438\u0439, \u043f\u0440\u043e\u0432\u043e\u0434\u0438\u043c\u044b\u0445 \u0432 \u043b\u0435\u0441\u0443 \u0438 \u043d\u0430 \u043f\u0440\u043e\u043c\u044b\u0448\u043b\u0435\u043d\u043d\u044b\u0445 \u0442\u0435\u0440\u0440\u0438\u0442\u043e\u0440\u0438\u044f\u0445 \u0433\u043e\u0440\u043e\u0434\u043e\u0432. \u041e\u0434\u043d\u0430\u043a\u043e \u0430\u043d\u0430\u043b\u0438\u0437 \u0441\u043d\u0438\u043c\u043a\u043e\u0432, \u043f\u043e\u043b\u0443\u0447\u0430\u0435\u043c\u044b\u0445 \u0441 \u043a\u0430\u043c\u0435\u0440 \u0434\u0440\u043e\u043d\u043e\u0432, \u0442\u0440\u0435\u0431\u0443\u0435\u0442 \u0432\u043e\u0432\u043b\u0435\u0447\u0435\u043d\u0438\u044f […]<\/p>\n","protected":false,"gt_translate_keys":[{"key":"rendered","format":"html"}]},"author":1,"featured_media":27733,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[702],"tags":[],"class_list":["post-37004","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-news"],"aioseo_notices":[],"aioseo_head":"\n\t\t\n\t\n\t\n\t\n\t\n\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\n","aioseo_head_json":{"title":"\ud83e\udd47The neural network \"Beeline AI - 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