Survey on Object Detection Algorithms using Neural Networks

Abstract

In day to day life, we encounter several different types of things like people, things, animals etc., but it becomes difficult for a system to identify them when processing them in images. For such identification purpose, we use Object Detection algorithms. These algorithms can be used for various uses like defence systems, security management units, and other fields like healthcare. In the following study, various Object Detection algorithms such as facial recognition, facial feature detection like skin, colour etc., and target detection have been performed and used to detect various types of objects with increased accuracy and efficiently in the fields like surveillance. Further, different difficulties and uses of Object Detection strategies are expounded. Pictures have numerous objects in complex foundation, how to distinguish these objects, the principle objects in that and comprehend the connection between them two that is, the primary objects and different objects are the significant focal point of this study. There are numerous ways which can be utilized for object detection and acknowledgment; however a large portion of them can’t check the primary objects of the picture. In the accompanying study, we are playing out a review on the different picture capturing strategies for object detection.