Analysis of Weapon and Fire Detectionon Different Datasets in Atms
Journal: IMPACT : International Journal of Research in Engineering & Technology ( IMPACT : IJRET ) (Vol.11, No. 1)Publication Date: 2023-01-31
Authors : R. Sathessh Kumar M. Dhinakaran Aditya Toamar Arpit Singh Afzal Khan Aditya Vajpayee;
Page : 1-7
Keywords : YOLOv3; Darknet; Video Processing; Anomaly Detection; Deep learning; Neural Networks;
Abstract
The special area of real-time objects moving according to monitoring methods is one of the sought-after reasons for CNNs. This review work is pushed into the field of shooting firearms and pistols in areas covered by cameras. Domestic fire incidents, current impacts and fast-spreading fires are major problems with negative environmental impacts. Gun cruelty and mass shootings are also on the rise in obvious places on the planet. Such events are time-consuming and can be a monstrous test of life and property. The proposed work has now generated a meaningful learning model that enables the YOLOv3 computation to process video images by tuning to rationally perceive those peculiarities and alert the experts. related.
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Last modified: 2023-06-07 13:06:49