{"id":402,"date":"2022-02-01T10:47:32","date_gmt":"2022-02-01T10:47:32","guid":{"rendered":"https:\/\/www2.kios.ucy.ac.cy\/ARTION\/?page_id=402"},"modified":"2025-02-13T08:03:34","modified_gmt":"2025-02-13T08:03:34","slug":"aerial-image-classification-for-drone-based-emergency-monitoring-emergencynet","status":"publish","type":"page","link":"https:\/\/www.kios.ucy.ac.cy\/ARTION\/aerial-image-classification-for-drone-based-emergency-monitoring-emergencynet\/","title":{"rendered":"Aerial Image Classification for Drone-based Emergency Monitoring (EmergencyNet)"},"content":{"rendered":"\n
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Developed by: Christos Kyrkou<\/p>\n\n\n\n

A small deep learning model based on atrous convolutional feature fusion for the application of emergency response.<\/p>\n\n\n\n

This algorithm[1] tackles the problem of on-board aerial scene classification and assigns automatically a semantic label to characterize an aerial image captured by a UAV. These labels will correspond to the type of danger or hazard that has occurred. Such a system can be deployed on UAVs for automated monitoring and inspection to enhance preparedness and provide rapid situational awareness. <\/p>\n\n\n\n

A detailed description of the algorithm can be found in the link where the software is available (provided below).<\/p>\n\n\n\n

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[1]<\/a> C. Kyrkou and T. Theocharides, “EmergencyNet: Efficient Aerial Image Classification for Drone-Based Emergency Monitoring Using Atrous Convolutional Feature Fusion,” in IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 13, pp. 1687-1699, 2020.<\/p>\n<\/div><\/div>\n\n\n\n

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Software<\/h3>\n<\/div>\n\n\n\n
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Code written in Python is available here: <\/p>\n\n\n\n

https:\/\/github.com\/ckyrkou\/EmergencyNet<\/a><\/p>\n<\/div>\n<\/div>\n<\/div><\/div>\n\n\n\n

<\/p>\n","protected":false},"excerpt":{"rendered":"

Developed by: Christos Kyrkou A small deep learning model based on atrous convolutional feature fusion for the application of emergency response. This algorithm[1] tackles the problem of on-board aerial scene classification and assigns automatically a semantic label to characterize an aerial image captured by a UAV. These labels will correspond to the type of danger… Continue reading Aerial Image Classification for Drone-based Emergency Monitoring (EmergencyNet)<\/span><\/a><\/p>\n","protected":false},"author":1,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-402","page","type-page","status-publish","hentry","entry"],"_links":{"self":[{"href":"https:\/\/www.kios.ucy.ac.cy\/ARTION\/wp-json\/wp\/v2\/pages\/402","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.kios.ucy.ac.cy\/ARTION\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/www.kios.ucy.ac.cy\/ARTION\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/www.kios.ucy.ac.cy\/ARTION\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.kios.ucy.ac.cy\/ARTION\/wp-json\/wp\/v2\/comments?post=402"}],"version-history":[{"count":3,"href":"https:\/\/www.kios.ucy.ac.cy\/ARTION\/wp-json\/wp\/v2\/pages\/402\/revisions"}],"predecessor-version":[{"id":414,"href":"https:\/\/www.kios.ucy.ac.cy\/ARTION\/wp-json\/wp\/v2\/pages\/402\/revisions\/414"}],"wp:attachment":[{"href":"https:\/\/www.kios.ucy.ac.cy\/ARTION\/wp-json\/wp\/v2\/media?parent=402"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}