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  1. Roboflow Blog
    https://blog.roboflow.com/a-thorough-breakdown-of-yolov4

    What is YOLOv4? A Detailed Breakdown. - Roboflow Blog

    • YOLOv4 is the fourth version in the You Only Look Once family of models. YOLOv4 makes realtime detection a priority and conducts training on a single GPU. The authors' intention is for vision engineer… See more

    Yolov4 Deep Dive: The Key Features

    How does YOLOv4 work? That's a great question! In this section, we're going to talk about how YOLOv4 works and the main features that comprise the model. See more

    Roboflow Blog
    Yolov4: Experimental Results

    The techniques in YOLOv4 were thoroughly proved out via experimentation on MS COCO. COCO contains 80 object classes and is meant to represent a broad range of object dete… See more

    Roboflow Blog
    Yolov4: Let's Get It Out There

    In sum, YOLOv4 is a distillation of a large suite of techniques for object detection in computer vision. These techniques have been tested and improved to form the best realtime obj… See more

    Roboflow Blog
    Frequently Asked Questions

    What is YOLOv4 used for?
    Like all other models in the YOLO family, the YOLOv4 model is used for object detection. Object detection problems are where you … See more

    Roboflow Blog
    What framework does yolov4 use?
    This implementation of YoloV4 uses the Darknet framework. By using YOLOv4, you are implementing many of the past research contributions in the YOLO family along with a series of new contributions unique to YOLOv4 including new features: WRC, CSP, CmBN, SAT, Mish activation, Mosaic data augmentation, CmBN, DropBlock regularization, and CIoU loss.
    roboflow.com
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    Table of Contents
    Yolov4 Deep Dive: The Key Features
    Yolov4: Experimental Results
    Yolov4: Let's Get It Out There
    Frequently Asked Questions
    What framework does yolov4 use?
     

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  2. YOLOv4 was a real-time object detection model published in April 2020 that achieved state-of-the-art performance on the COCO dataset. It works by breaking the object detection task into two pieces, regression to identify object positioning via bounding boxes and classification to determine the object's class.

    YOLOv4 Darknet Object Detection Mod…

    roboflow.com/model/yolov4
    YOLOv4 stands for You Only Look Once version 4. It is a real-time object detection model developed to address the limitations of previous YOLO versions like YOLOv3 and other object detection models.

    YOLOv4 - Ultralytics YOLOv8 Docs

    docs.ultralytics.com/models/yolov4/
     
  3. People also ask
    Does yolov4 outperform other object detection network architectures?
    Bochkovskiy et al. (2020) did extensive experiments across different GPU architectures and showed that YOLOv4 outperformed all the other object detection network architectures in terms of speed and accuracy.

    Achieving Optimal Speed and Accuracy in Object Detection (YOLOv4)

    pyimagesearch.com
    How effective is yolov4?
    It was proved effective in the backbone of various practical object detectors like YOLOv4 and YOLOv5. Larger Input Size: Detecting smaller objects is often a challenge, and as the image traverses through the network, the information of the objects on a small scale is lost.

    Introduction to the YOLO Family - PyImageSearch

    pyimagesearch.com
    What framework does yolov4 use?
    This implementation of YoloV4 uses the Darknet framework. By using YOLOv4, you are implementing many of the past research contributions in the YOLO family along with a series of new contributions unique to YOLOv4 including new features: WRC, CSP, CmBN, SAT, Mish activation, Mosaic data augmentation, CmBN, DropBlock regularization, and CIoU loss.

    YOLOv4 Darknet Object Detection Model: What is, How to Use - Roboflow

    roboflow.com
    How yolov4 architecture was selected?
    You then learned the post-processing methods and plugin modules called “Bag of Specials,” which improve the detector’s accuracy with minimal effect on the inference speed. We then discussed how YOLOv4 Architecture was selected: the backbone it used, the Neck with additional blocks, and the YOLOv2 head for object detection.

    Achieving Optimal Speed and Accuracy in Object Detection (YOLOv4)

    pyimagesearch.com
    What is new in yolov4?
    YOLOv4’s architecture is composed of CSPDarknet53 as a backbone, spatial pyramid pooling additional module, PANet path-aggregation neck and YOLOv3 head. CSPDarknet53 is a novel backbone that can enhance the learning capability of CNN.

    What’s new in YOLOv4? - Towards Data Science

    towardsdatascience.com
    How do I install yolov4?
    To get started with YOLOv4, you should visit the official YOLOv4 GitHub repository. Follow the installation instructions provided in the README file, which typically include cloning the repository, installing dependencies, and setting up environment variables.

    YOLOv4 - Ultralytics YOLO Docs

    docs.ultralytics.com
    Feedback
     
  4. Github
    https://github.com/AlexeyAB/darknet

    AlexeyAB/darknet: YOLOv4 / Scaled-YOLOv4 / YOLO - GitHub

     
  5. Roboflow
    https://roboflow.com/model/yolov4

    YOLOv4 Darknet Object Detection Model: What is, How to Use

  6. PyImageSearch
    https://pyimagesearch.com/2022/05/16…

    Achieving Optimal Speed and Accuracy in Object …

    May 16, 2022 · In this tutorial, you will learn all about YOLOv4 from a research perspective as we will dive deeper into the workings of this accurate and fast object detection network. We would build the intuition by comparing this …

  7. Papers With Code
    https://paperswithcode.com/method/yolov4

    YOLOv4 Explained - Papers With Code

  9. Roboflow Blog
    https://blog.roboflow.com/yolov4-tactics

    YOLOv4 - Ten Tactics to Build a Better Model - Roboflow Blog

  10. arXiv.org
    https://arxiv.org/abs/2004.10934

    Title: YOLOv4: Optimal Speed and Accuracy of Object Detection

  11. arXiv.org
    https://arxiv.org/html/2304.00501v6

    A Comprehensive Review of YOLO Architectures in Computer …

  12. arXiv.org
    https://arxiv.org/pdf/2304.00501v1
    [PDF]

    A Comprehensive Review of YOLO: From YOLOv1 to …

  13. Towards Data Science
    https://towardsdatascience.com/whats-new-in-yolov4-323364bb3ad3

    What’s new in YOLOv4?. YOLO is a real-time object …

  14. Ultralytics YOLOv8 Docs
    https://docs.ultralytics.com/models/yolov4

    YOLOv4 - Ultralytics YOLO Docs

  15. Medium
    https://medium.com/aiguys/yolo-v4-explained-in...

    YOLO v4 explained in full detail | AIGuys - Medium

  16. DataCamp
    https://www.datacamp.com/blog/yolo-object-detection-explained

    YOLO Object Detection Explained: A Beginner's Guide

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

    Introduction to the YOLO Family - PyImageSearch

  18. Nature
    https://www.nature.com/articles/s41598-023-47398-w

    Keypoint regression strategy and angle loss based YOLO for …

  19. Roboflow Blog
    https://blog.roboflow.com/training-yolov4-on-a-custom-dataset

    How to Train YOLOv4 on a Custom Dataset - Roboflow Blog

  20. arXiv.org
    https://arxiv.org/pdf/2209.02976
    [PDF]

    arXiv:2209.02976v1 [cs.CV] 7 Sep 2022

  21. Roboflow Blog
    https://blog.roboflow.com/a-new-video-tutorial-yolov4-in-pytorch

    A New Video Tutorial: YOLOv4 in PyTorch - Roboflow Blog

  22. Medium
    https://medium.com/axinc-ai/yolov4-a-machine...

    YOLOv4 : A Machine Learning Model to Detect the Position and …