{"id":671,"date":"2024-04-24T13:44:20","date_gmt":"2024-04-24T13:44:20","guid":{"rendered":"http:\/\/www.ub.edu\/cvub\/?post_type=project&#038;p=671"},"modified":"2024-05-08T08:23:30","modified_gmt":"2024-05-08T08:23:30","slug":"fooddeep","status":"publish","type":"project","link":"https:\/\/www.ub.edu\/aiba\/project\/fooddeep\/","title":{"rendered":"FoodDeep"},"featured_media":672,"template":"","class_list":["post-671","project","type-project","status-publish","has-post-thumbnail","hentry"],"acf":{"summary":"A digital tool for estimating the amount of food using deep learning - [2022 - 2024]\r\n\r\nKey Words: Deep Learning, Food Data Analysis, Image Segmentation, Food Volume Estimation","full_content":"<p><strong>Name of the project:<\/strong> <span style=\"font-weight: 400;\">A digital tool for estimating the amount of food using deep learning<\/span><\/p>\n<p><strong>Name principal investigator (PI):<\/strong> Petia Radeva<\/p>\n<p><strong>Funding entity:<\/strong> <span style=\"font-weight: 400;\">Ministry of Science and Innovation<\/span><\/p>\n<p><b>Duration: <\/b><span style=\"font-weight: 400;\">01\/12\/2022 &#8211; 30\/11\/2024<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Why Food recognition and Food Volume Estimation? Today we live in conditions of increasing work stress and hectic lifestyle that inherently have adverse effects on our health. Fortunately, there is a rise in awareness of the importance of maintaining health via good eating habits and exercises.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">A digital tool for estimating the amount of food using deep learning. The aim of DeepFoodVol is to optimise from the point of view of time running, extensively test and generate a prototype of our Deep learning algorithms to be integrated into an innovative dietary assessment application tool ready to provide precise feedback on user\u2019s food intake and nutritional status.<\/span><\/p>\n","members":[{"ID":18,"post_author":"1","post_date":"2021-03-01 14:40:03","post_date_gmt":"2021-03-01 14:40:03","post_content":"","post_title":"Petia I. Radeva","post_excerpt":"","post_status":"publish","comment_status":"closed","ping_status":"closed","post_password":"","post_name":"petia-radeva","to_ping":"","pinged":"","post_modified":"2024-10-29 09:11:01","post_modified_gmt":"2024-10-29 09:11:01","post_content_filtered":"","post_parent":0,"guid":"http:\/\/cvml.localhost\/?post_type=member&#038;p=18","menu_order":1,"post_type":"member","post_mime_type":"","comment_count":"0","filter":"raw"}],"research_lines":[{"ID":63,"post_author":"1","post_date":"2021-06-13 18:24:34","post_date_gmt":"2021-06-13 18:24:34","post_content":"","post_title":"Deep learning for food computing","post_excerpt":"","post_status":"publish","comment_status":"closed","ping_status":"closed","post_password":"","post_name":"deep-learning-for-food-computing","to_ping":"","pinged":"","post_modified":"2024-03-12 13:31:14","post_modified_gmt":"2024-03-12 13:31:14","post_content_filtered":"","post_parent":0,"guid":"http:\/\/cvml.localhost\/?post_type=research_line&#038;p=63","menu_order":2,"post_type":"research_line","post_mime_type":"","comment_count":"0","filter":"raw"}]},"_links":{"self":[{"href":"https:\/\/www.ub.edu\/aiba\/wp-json\/wp\/v2\/project\/671","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.ub.edu\/aiba\/wp-json\/wp\/v2\/project"}],"about":[{"href":"https:\/\/www.ub.edu\/aiba\/wp-json\/wp\/v2\/types\/project"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.ub.edu\/aiba\/wp-json\/wp\/v2\/media\/672"}],"wp:attachment":[{"href":"https:\/\/www.ub.edu\/aiba\/wp-json\/wp\/v2\/media?parent=671"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}