Faster Region Based Convolutional Neural Networks News Today : Breaking News, Live Updates & Top Stories | Vimarsana

Computer vision technology for detecting objects in a complex environment often includes other key technologies, including pattern recognition, artificial intelligence, and digital image processing. It has been shown that Fast Convolutional Neural Networks (CNNs) with You Only Look Once (YOLO) is optimal for differentiating similar objects, constant motion, and low image quality. The proposed study aims to resolve these issues by implementing three different object detection algorithms You Only Look Once (YOLO), Single Stage Detector (SSD), and Faster Region-Based Convolutional Neural Networks (R-CNN). This paper compares three different deep-learning object detection methods to find the best possible combination of feature and accuracy. The R-CNN object detection techniques are performed better than single-stage detectors like Yolo (You Only Look Once) and Single Shot Detector (SSD) in term of accuracy, recall, precision and loss. ....

Fast Convolutional Neural Networks Cnns , Convolutional Neural Networks , Fast Convolutional Neural Networks , Only Look Once , Single Stage Detector , Faster Region Based Convolutional Neural Networks , Single Shot Detector , Chess Piece Identification , Aster Region Based Convolutional Neural Networksr Cnn , Object Detection , Ingle Stage Detector Ssd , Ou Only Look Once Yolo ,