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Automatic Handgun Detection Alarm in VideosUsing Deep LearningRoberto Olmos1, Siham Tabik1, and Francisco Herrera1,21 Soft Computing and Intelligent Information Systems researchgroup2 Department of Computer Science and Artificial Intelligence,University of granada , 18071 granada , Spain. 20, 2017 AbstractCurrent surveillance and control systems still require human super-vision and intervention. This work presents a novel Automatic handgundetection system in Videos appropriate for both, surveillance and con-trol purposes. We reformulate this Detection problem into the problemof minimizing false positives and solve it by building the key trainingdata-set guided by the results of a deep Convolutional Neural Networks(CNN) classifier, then assessing the best classification model under twoapproaches, the sliding window approach and region proposal most promising results are obtained by Faster R-CNN based modeltrained on our new database. The best detector show a high potential evenin low quality youtube Videos and provides satisfactory results as auto-matic Alarm system.
Automatic Handgun Detection Alarm in Videos Using Deep Learning Roberto Olmos 1, Siham Tabik , and Francisco Herrera1,2 1Soft Computing and Intelligent Information Systems research group 2Department of Computer Science and Arti cial Intelligence, University of Granada, 18071 Granada, Spain. emails: siham@ugr.es, herrera@decsai.ugr.es
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