• 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

  • From page
    46
  • To page
    64
  • 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
  • Record number

    2572327