CRIM’s project, carried out via the National Defense IDEeS program, aims to assess the state of operators non-intrusively using AI and computer vision. The new technique uses facial emotion analysis to assess a person’s emotional state using a deep learning model. <\/p>\n
The development of a reliable, non-intrusive technique would make it easy to monitor the psychological state of individual operators, and avoid mental overload that could lead to incidents.<\/p>\n
Additional information: <\/strong>AI detects emotional state of drone operators – CScience.ca – March 3, 2021<\/a><\/p>\n Mohamed Dahmane,<\/strong> a computer vision researcher at CRIM, will offer a master class on the subject: Multimodal detection of emotions and stress in drone operators using deep learning Operators of drones and remotely piloted aircraft have a demanding job, with many challenges. As UAVs ( unmanned aerial vehicles) become increasingly autonomous, the number of personnel at the controls during missions is reduced. But this also poses safety challenges, as control and […]<\/p>\n","protected":false},"author":18,"featured_media":9484,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":"","_links_to":"","_links_to_target":""},"categories":[81],"tags":[187,183,185,182],"class_list":["post-2957","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-news","tag-computer-vision","tag-deep-learning","tag-drone-en","tag-emotion-analysis"],"acf":[],"_links":{"self":[{"href":"https:\/\/www.crim.ca\/en\/wp-json\/wp\/v2\/posts\/2957","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.crim.ca\/en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.crim.ca\/en\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.crim.ca\/en\/wp-json\/wp\/v2\/users\/18"}],"replies":[{"embeddable":true,"href":"https:\/\/www.crim.ca\/en\/wp-json\/wp\/v2\/comments?post=2957"}],"version-history":[{"count":6,"href":"https:\/\/www.crim.ca\/en\/wp-json\/wp\/v2\/posts\/2957\/revisions"}],"predecessor-version":[{"id":28582,"href":"https:\/\/www.crim.ca\/en\/wp-json\/wp\/v2\/posts\/2957\/revisions\/28582"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.crim.ca\/en\/wp-json\/wp\/v2\/media\/9484"}],"wp:attachment":[{"href":"https:\/\/www.crim.ca\/en\/wp-json\/wp\/v2\/media?parent=2957"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.crim.ca\/en\/wp-json\/wp\/v2\/categories?post=2957"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.crim.ca\/en\/wp-json\/wp\/v2\/tags?post=2957"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}
\nHuman factors in autonomous system operators: AI in the loop.
\n<\/strong>As part of CRIAQ’s RDV Forum on February 19, 2021 at 1:30pm. Register here<\/strong><\/a><\/span><\/p>\n![\"CRIM](\"https:\/\/www.crim.ca\/\/wp-content\/uploads\/2021\/02\/cours-maitre-crim-criaq-2021.png\")
<\/p>\n<\/h6>\n
Scientific publication about the project : <\/strong><\/h6>\n
M. Dahmane, J. Alam, P. St-Charles, M. Lalonde, K. Heffner and S. Foucher, “A Multimodal Non-Intrusive Stress Monitoring from the Pleasure-Arousal Emotional Dimensions<\/a><\/span>” in IEEE Transactions on Affective Computing, April 20, 2020.<\/h6>\n","protected":false},"excerpt":{"rendered":"