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  5. People also ask
    What is yolov4?YOLOv4 was designed for real-time object detection on a general GPU. In Scaled-YOLOv4, the YOLOv4 is re-designed to YOLOv4-CSP to get the best speed/accuracy trade-off.

    Introduction to the YOLO Family - PyImageSearch

    pyimagesearch.com
    Which yolov3-lit model has the best performance?Considering the precision, recall rate, and F1 score together, Trial 17 yielded the best performance (Mixed YOLOv3-LITE) by achieving 49.53%, 69.54%, and 57.85% for the above indices, respectively. The amount of computation of the model was 2.48 GFLOPs, which is only 13% of that of YOLOv3.

    Mixed YOLOv3-LITE: A Lightweight Real-Time Object Detection Method

    ncbi.nlm.nih.gov
    What are the evaluation results for yolov3 & mixed Yolo Lite for shipdata?Evaluation results for YOLOv3 and Mixed YOLOv3-LITE for ShipData. 4.2.4. Performance Tests Based on Embedded Platform Mixed YOLOv3-LITE was tested with a Jetson AGX Xavier device; the results are shown in Table 10. When inputting an image with a size of 224 × 224, it reached 43 FPS.

    Mixed YOLOv3-LITE: A Lightweight Real-Time Object Detection Method

    ncbi.nlm.nih.gov
    What is yolov3?Redmon and Farhadi (2018) published the YOLOv3: An Incremental Improvement paper on arXiv. The authors made many design changes concerning the network architecture and adapted most of the other techniques from YOLOv1 and especially YOLOv2. This paper introduced a new network architecture called Darknet-53.

    Introduction to the YOLO Family - PyImageSearch

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  6. DBREE
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  7. Github
    https://github.com/kiyoshiiriemon/yolov4_darknet

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  8. DBREE
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  9. DBREE
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  14. arXiv.org
    https://arxiv.org/pdf/2005.13243
    [PDF]

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  15. Github
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  17. PyImageSearch
    https://pyimagesearch.com/2022/04/04/introduction-to-the-yolo-family

    Introduction to the YOLO Family - PyImageSearch

  18. Github
    https://github.com/topics/yolov4

    yolov4 · GitHub Topics · GitHub

  19. Github
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  20. National Center for Biotechnology Information
    https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7180807

    Mixed YOLOv3-LITE: A Lightweight Real-Time Object Detection …

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