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Revolutionizing Object Detection with Yolo v4(medium.com)

123 points by codewizard 1 year ago | flag | hide | 19 comments

  • johnsmith 1 year ago | next

    Great article on YOLO v4! I've been experimenting with it myself and it's amazing how accurate and fast it is compared to previous versions.

  • newuser 1 year ago | prev | next

    I'm new to computer vision, can someone explain what makes YOLO v4 different from other object detection algorithms?

    • jane456 1 year ago | next

      YOLO v4 is faster and more accurate due to several improvements, such as a new backbone, altered neck, and new head.

  • techie123 1 year ago | prev | next

    Is there any implementation that users can try it out without having to code everything from scratch?

    • peterpan 1 year ago | next

      Yes, there are several pre-trained models available online. Try out the Ultralytics' YOLOv4 repo on GitHub for starters.

  • wonderwoman 1 year ago | prev | next

    What's the performance difference between YOLOv3 and YOLOv4?

    • codemaster1 1 year ago | next

      YOLOv4 has an AP (Average Precision) that is 10% higher than YOLOv3, while being significantly faster as well.

  • jane456 1 year ago | prev | next

    I've heard that YOLO v4 uses much more data for training, is this true?

    • techie123 1 year ago | next

      Yes, YOLO v4 uses the CSPDarknet53 backbone and has an extremely large number of layers. The authors found that training on large datasets (including COCO and the large YouTube-BB dataset) helped improve results tremendously.

  • wonderwoman 1 year ago | prev | next

    Any plans to release further updates like YOLOv5?

    • peterpan 1 year ago | next

      The Ultralytics' YOLO v4 team has their roadmap published on GitHub. They've already introduced YOLOv5 in the beta stage for those interested in testing it out.

  • newuser 1 year ago | prev | next

    What hardware requirements would you recommend for using YOLOv4 effectively?

    • johnsmith 1 year ago | next

      To fully take advantage of YOLOv4's performance, I'd suggest using a powerful GPU like the NVIDIA RTX 2080Ti or higher. It's designed to optimize deep neural networks and offers a significant speedup compared to CPU processing.

  • codemaster 1 year ago | prev | next

    How does YOLO v4 compare to other object detection models like EfficientDet and CenterNet?

    • johnsmith 1 year ago | next

      YOLO v4 outperforms EfficientDet and CenterNet on both accuracy (AP) and speed. However, specific performance metrics may vary depending on your hardware and implementation.

  • techie123 1 year ago | prev | next

    What's the general consensus of the computer vision community about YOLO v4's future and further improvements?

    • jane456 1 year ago | next

      As YOLO v4 already offers tremendous performance enhancements, I think most researchers have turned their focus to niche areas such as real-time semantic segmentation and LiDAR-based object detection. That said, YOLO v4 is still a hot topic and articles and papers discussing improvements or alternatives are frequently published.

  • captain 1 year ago | prev | next

    Impressive progress on YOLO v4, I'm excited about its potential applications in autonomous vehicles and security systems. Thanks for the informative discussion!

  • johnsmith 1 year ago | prev | next

    You're welcome! The rapid advancements in computer vision technology are truly exciting, and YOLO v4 is just a tipping point for what's yet to come. Keep an eye out for further developments in real-time AI applications.