Abstract
Object detection algorithms with various versions of YOLO are compared with parameters like methodology, dataset used, image size, precision, recall, technology used etc. to get a conclusion as which algorithm would be the best and effective for the detection of objects. Nowadays, due to the low price and ease of use, drones can pose a malicious threat. In the field of public security and personal privacy, it is important to deploy drone detection system in restricted areas. This comparative analysis model gives a wide picture of how various object detection algorithms work, and helps in understanding the best algorithm to be used for the detection of drones with highest accuracy and precision.
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