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YOLO (You Only Look Once) is an object detection algorithm that can identify and locate multiple objects in an image or frame in a single forward pass through a convolutional neural network (CNN).
The "Detection" objective involves the system's ability to accurately locate and identify weapons in images or videos, providing real-time responses in security or law enforcement scenarios, while also maintaining reliability and adaptability under various conditions.
Presented by
Harivarsh Joshi (2VD20EC021)
Kartik M Pented (2VD20EC023)
Navinya J Aikal (2VD20EC033)
Noopur k Mahendrakar (2VD20EC038)
Weapon detection using YOLOv5 is a computer vision application that leverages the YOLO (You Only Look Once) deep learning architecture, specifically the YOLOv5 variant,
YOLOv5 is an improved and more efficient version of the YOLO series of object detection models, known for its real-time and accurate object detection capabilities.