A Comparative Study of Various Object Detection Algorithms and Performance Analysis
DOI:
https://doi.org/10.26438/ijcse/v8i10.158163Keywords:
Object Detection, Object Finding, R-CNN, Fast RCNN, Faster RCNN, Single Shot Detector, YOLO v3Abstract
Object finding is a fast-developing technique in the area of Computer Vision and Machine Learning. Computer vision is one of the principal tasks of deep learning field. Object detection is a technique that identifies the existence of object in an image or video. Object detection can be used in many areas for improving efficiency in the task. The applications for object detection are in home automation, self-driving cars, people counting, agriculture, traffic monitoring, military defence systems, sports, industrial work, robotics, aviation industry and many others. Object detection can be done through various techniques like R-CNN, Fast R-CNN, Faster R-CNN, Single Shot detector (SSD) and YOLO v3. A comparison of these algorithms is done and also their results as well as performance is analysed. The performance and exactness should be utmost important in analysing the algorithms.
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