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 surrounding objects in real-time surroundings. This paper describes the usage of methods of deep learning using convolutional type of Neural Networks intended for computer vision applications. This study goes one step further and tackles the issue of object detection by Deep Neural Networks, the strategy is not just based on segregating classes but additionally localize the different objects to various classes precisely. The work aims at providing observations and conclusions primarily based on a real-time object 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 and inferences show that SSD is a much better real-time model.