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  2. Github
    https://github.com/kiyoshiiriemon/yolov4_darknet

    kiyoshiiriemon/yolov4_darknet: YOLOv4 - GitHub

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    Install and run YOLOv4-Darknet on Windows (For GPU!) - …
    youtube.com
    Yolov4 weights · Issue #2135 · pjreddie/darknet · GitHub
    github.com
    OpenCV YoloV4-tiny weights and .cfg file? - Stack Overflow
    stackoverflow.com
    Darknet YOLO download | SourceForge.net
    sourceforge.net
    LinkonBSMRSTU/Real-time-YOLOv4-and-Darknet-Object …
    github.com
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  3. Github
    https://github.com/augmentedstartups/YOLOv4...

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  4. bris.ac.uk
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  5. Github
    https://github.com/LinkonBSMRSTU/Real-ti…

    Implement YOLOv4 Object Detection on your …

    WEBAbout. Implement YOLOv4 Object Detection on your Webcam from within Google Colab! This tutorial uses scaled-YOLOv4, the most fast and accurate object detection system there currently is. Perform object …

  6. Towards Data Science
    https://towardsdatascience.com/yolov2-for-object...

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  7. Nature
    https://www.nature.com/articles/s41598-021-02225-y

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  8. People also ask
    How do I create an OBJ file for yoltv4?To create an OBJ file for yoltv4, first make YOLO images and labels (see yoltv4/notebooks/train_test_pipeline.ipynb for further details). Create a txt file listing the training images. Next, create file obj.names with each desired object name on its own line. Lastly, create file obj.data in the directory yoltv4/darknet/data containing the necessary files.

    GitHub - avanetten/yoltv4: Better, faster, peering over yonder

    github.com
    What are the new features in yoltv4?GitHub - avanetten/yoltv4: Better, faster, peering over yonder. YOLTv4 improves large scale object detection in aerial/satellite imagery and builds upon YOLT and SIMRDWN by updating these frameworks to use the most performant version of YOLO, YOLOv4.

    GitHub - avanetten/yoltv4: Better, faster, peering over yonder

    github.com
    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
    How do I use yoltv4?To use yoltv4, first, clone this repository (e.g. to /yoltv4/), then download model weights to yoltv4/darknet/weights. YOLTv4 is designed to run within a docker container on a GPU-enabled machine. The docker command creates an Ubuntu 16.04 image with CUDA 9.2, python 3.6, and conda.

    GitHub - avanetten/yoltv4: Better, faster, peering over yonder

    github.com
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  9. arXiv.org
    https://arxiv.org/pdf/2005.13243
    [PDF]

    y arXiv:2005.13243v2 [cs.CV] 29 May 2020

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  13. 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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  19. Github
    https://github.com/topics/yolobit

    yolobit · GitHub Topics · GitHub

  20. Wikipedia
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  21. Github
    https://github.com/avanetten/yoltv4

    GitHub - avanetten/yoltv4: Better, faster, peering over yonder ...

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  23. simivalleyusd.org
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  24. Github
    https://github.com/ultralytics/yolov5/issues/7566

    Show Video MP4 · Issue #7566 · ultralytics/yolov5 · GitHub

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