Object Detection Using Convolutional Neural Networks: A Comprehensive Review

With advances in technology, the issue of object detection and recognition has gained significant recognition in the field of computer vision. There are currently several algorithms that address this growing demand, namely region-based convolutional neural networks (R-CNN) and the You Only Look Once (YOLO) technique. The R-CNN technique encompasses a range of methodologies designed to address object localization and recognition tasks. In addition, the YOLO technique is a distinct set of methodologies that focuses primarily on real-time object recognition and fast performance. The R-CNN and YOLO techniques, in particular, have undergone subsequent improvements, resulting in higher levels of accuracy and performance than their predecessors. The aim of this article is to review these various object detection methods based on CNN.