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  1. Roboflow Blog
    https://blog.roboflow.com

    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 is Yolo framework?
    Q1.What is the Yolo framework? YOLO (You Only Look Once) is a real-time object detection framework that rapidly identifies objects in images or video streams. It employs a single neural network to simultaneously predict bounding boxes and class probabilities.
    analyticsvidhya.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 is Yolo framework?
     

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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
    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
    What is Yolo framework?
    Q1.What is the Yolo framework? YOLO (You Only Look Once) is a real-time object detection framework that rapidly identifies objects in images or video streams. It employs a single neural network to simultaneously predict bounding boxes and class probabilities.

    Yolo Framework : Object Detection Using Yolo - Analytics Vidhya

    analyticsvidhya.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?
    Additionally, a novel angle loss (AL) function is designed to adapt to the new regression strategy, effectively updating the network model parameters and enhancing algorithm accuracy. Improved feature fusion techniques are also introduced to reinforce the original feature fusion in YOLOv4.

    Keypoint regression strategy and angle loss based YOLO for object det…

    nature.com
    What modules are included in yolov4?
    Terms and conditions apply. Block diagram of YOLOv4 object detection. The small modules included are CBM: Convolution + Batch Normalization + Mish; CBL: Convolution + Batch Normalization + Leaky ReLU; and UP: Upsampling [...]

    Block diagram of YOLOv4 object detection. The small ... - ResearchGate

    researchgate.net
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  4. PyImageSearch
    https://pyimagesearch.com › achieving...

    Achieving Optimal Speed and Accuracy in Object …

    WEBMay 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 …

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

    YOLO Object Detection Explained: A Beginner's Guide

  6. Github
    https://github.com › AlexeyAB › darknet

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

  7. arXiv.org
    https://arxiv.org › html

    A Comprehensive Review of YOLO Architectures in Computer …

  8. Roboflow
    https://roboflow.com › model

    YOLOv4 Darknet Object Detection Model: What is, …

    WEBWhat is YOLOv4? YOLOv4 was a real-time object detection model published in April 2020 that achieved state-of-the-art performance on …

    • Reviews: 1
    • Medium
      https://medium.com › aiguys

      YOLO v4 explained in full detail | AIGuys - Medium

      WEBDec 23, 2021 · YOLOv4 architecture selection; YOLOv4 BoF and BoS selection; Object detector architecture breakdown. The original YOLO (You Only Look Once) was written by Joseph Redmon in a custom...

    • arXiv.org
      https://arxiv.org › pdf
      [PDF]

      A Comprehensive Review of YOLO: From YOLOv1 to …

    • Ultralytics YOLOv8 Docs
      https://docs.ultralytics.com › models

      YOLOv4 - Ultralytics YOLO Docs

    • Github
      https://github.com › jch-wang

      jch-wang/YOLOV4-C-official-AlexeyAB: YOLOv4

      WEBMake your custom model yolov4-tiny-obj.cfg based on cfg/yolov4-tiny-custom.cfg instead of yolov4.cfg; Start training: darknet.exe detector train data/obj.data yolov4-tiny-obj.cfg yolov4-tiny.conv.29

    • arXiv.org
      https://arxiv.org › abs

      Title: YOLOv4: Optimal Speed and Accuracy of Object Detection

    • Roboflow Blog
      https://blog.roboflow.com

      How to Train YOLOv4 on a Custom Dataset - Roboflow Blog

    • PyImageSearch
      https://pyimagesearch.com › introduction-to-the-yolo-family

      Introduction to the YOLO Family - PyImageSearch

    • OpenGenus IQ
      https://iq.opengenus.org

      YOLOv4 model architecture - OpenGenus IQ

    • Nature
      https://www.nature.com › articles

      Keypoint regression strategy and angle loss based YOLO for …

    • Analytics Vidhya
      https://www.analyticsvidhya.com › blog

      Yolo Framework : Object Detection Using Yolo - Analytics Vidhya

    • Github
      https://github.com › Lornatang

      GitHub - Lornatang/YOLOv4-PyTorch: Pytorch implements …

    • Medium
      https://medium.com

      Working of YOLOv4 Algorithm - Medium

    • IEEE Xplore
      https://ieeexplore.ieee.org › document

      Vehicle Tracking based on an Improved DeepSORT Algorithm …

    • National Center for Biotechnology Information
      https://www.ncbi.nlm.nih.gov › pmc › articles

      Comparing YOLOv3, YOLOv4 and YOLOv5 for Autonomous …

    • ResearchGate
      https://www.researchgate.net › figure

      Block diagram of YOLOv4 object detection. The small

    • Github
      https://github.com › hank-ai › darknet

      hank-ai/darknet: Darknet/YOLO object detection framework - GitHub

    • Data Science Stack Exchange
      https://datascience.stackexchange.com › questions

      what is darknet and why is it needed for YOLO object detection?

    • Nature
      https://www.nature.com › articles

      Development of intelligent suite for malaria pathogen detection in ...

    • MDPI
      https://www.mdpi.com

      Lightweight Detection of Broccoli Heads in Complex Field ... - MDPI

    • ScienceDirect
      https://www.sciencedirect.com › science › article › pii

      Hybrid segmentation and 3D Imaging: Comprehensive framework …

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