-This paper spotlight on the real time detection and recognition model called as YOLO. It uses single convolutional neural network in order to detect and recognize the objects of the images. The model is first trained on COCO dataset and car dataset of achieving a mAP of 91.28% and 70% respectively. YOLO takes 57 FPS to processes the image to detect the objects in Image. Since YOLO takes whole detection pipeline in a single unified network and it helps to increase and optimize the real time object detection with variety of objects.
Paper
Full text
Deep Learning Based Object Detection Using You Only Look Once
Semantic Scholar · Computer Science · 2019
Abstract
-This paper spotlight on the real time detection and recognition model called as YOLO. It uses single convolutional neural network in order to detect and recognize the objects of the images. The model is first trained on COCO dataset and car dataset of achieving a mAP of 91.28% and 70% respectively. YOLO takes 57 FPS to processes the image to detect the objects in Image. Since YOLO takes whole detection pipeline in a single unified network and it helps to increase and optimize the real time object detection with variety of objects.