Analysis of Various Algorithms in Low Light Conditions
This paper aims to compare the different object detection algorithms and image classifiers on the basis of latency and accuracy using low light images. Object detection algorithms are used in various systems like self-driving cars, traffic monitoring, surveillance etc. So choosing an algorithm with a good balance of accuracy and latency becomes a major task. We have compared two image classifier algorithms, i.eEfficientNet, MobileNet and two Object detection algorithms YOLOv4 and Mask R-CNN(Region-based Convolutional Neural Network).
Keywords - MobileNet, EfficientNet, Mask R-CNN, YOLOv4.