Deep Neural Networks based Object Detection by Single Shot Detector Model - Nagaraj Bhat, Madhusudan Kulkarni,Santosh M Herur (International Journal of Advanced Science and Technology, 2020)
Automated systems need dependable, meticulous detection as well as recognition of surroundingobjects in real-time surroundings. This paper describes the usage of methods of deep learning usingconvolutional type of Neural Networks intended for computer vision applications. This study goes onestep further and tackles the issue of object detection by Deep Neural Networks, the strategy is not justbased on segregating classes but additionally localize the different objects to various classesprecisely. The work aims at providing observations and conclusions primarily based on a real-timeobject detection approach trained by the use of single Shot detector(SSD) model. With addition,evaluating the SSD model together with other popular models like Faster R-CNN is carried out andinferences show that SSD is a much better real-time model.