Title of article :
Comparative analysis on YOLO object detection with OpenCV
Author/Authors :
Deshpande ، H. Department of Computer Application - Jain (Deemed to-be) University , Singh ، A. Department of Computer Application - Jain (Deemed to-be) University , Herunde ، H. Department of Computer Application - Jain (Deemed to-be) University
Abstract :
Computer Vision is a field of study that helps to develop techniques to identify images and displays. It has various features like image recognition, object detection and image creation, etc. Object detection is used for face detection, vehicle detection, web images, and safety systems. Its algorithms are Region-based Convolutional Neural Networks (RCNN), Faster-RCNN and You Only Look Once Method (YOLO) that have shown state-of-the-art performance. Of these, YOLO is better in speed compared to accuracy. It has efficient object detection without compromising on performance.
Keywords :
YOLO , Faster , RCNN , Convolutional neural network , COCO
Journal title :
International Journal of Research in Industrial Engineering
Journal title :
International Journal of Research in Industrial Engineering