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OpenGenus IQ
https://iq.opengenus.org/yolov4-model-architecture
YOLOv4 model architecture - OpenGenus IQ
YOLOv4 is a SOTA (state-of-the-art) real-time Object Detection model. It was published in April 2020 by Alexey Bochkovsky; it is the 4th installment to YOLO. It achieved SOTA performance on the COCO dat… See more
Brief Introduction to Object Detection
Before we proceed further, we'll understand the task of object detection. The standard definition from Wikipedia goes like, The task of object detection consists of two things - th… See more
OpenGenus IQ
Algorithm Overview
The architecture consists of various parts, broadly they are - The input which comes first and it is basically what we've as our set of training images which will be fed to the network - t… See more
OpenGenus IQ
Backbone Network
The authors initially considered CSPResNext50, CSPDarknet53 and EfficientNet-B3 as the backbone networks. Finally, after a lot of testing and experiment… See more
OpenGenus IQ
Neck
The neck is the part where feature aggregation takes place. It collects feature maps from the different stages of the backbone then mixes and combines them to prepare t… See more
OpenGenus IQ
How fast is Yolo V4?
This makes it possible to train a super fast and accurate object detector with a single 1080 Ti or 2080 Ti GPU. YOLO v4 achieves state-of-the-art results at a real time speed on the MS COCO dataset with 43.5 % AP running at 65 FPS on a Tesla V100. Pretty interesting results!
towardsdatascience.com
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Table of Contents
Brief Introduction to Object Detection
Algorithm Overview
Backbone Network
Neck
How fast is Yolo V4?

Bokep
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Roboflow Blog
https://blog.roboflow.com/a-thorough-breakdown-of-yolov4
What is YOLOv4? A Detailed Breakdown. - Roboflow Blog
WEBJan 4, 2024 · Learn more about YOLOv8 in our architectural breakdown and how to train a YOLOv8 model guides. The realtime object detection space remains hot and moves …
- Estimated Reading Time: 11 mins
Images of YOLO v4 model

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analyticsvidhya.com
YOLO V4 | Social Distancing and Face Mask Detection using YOLO V4
researchgate.net
Overall structure of YOLOv4, including CSPDarknet (backbone), SPPnet ...
wikidocs.net
C_5. Yolo V4 explained in full detail - Deep Learning Bible - 4. Object ...
aiophotoz.com
How To Train A Scaled Yolov4 Object Detection Model Yolov3 Real Time ...
medium.com
YOLO v4 explained in full detail | AIGuys
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Papers With Code
https://paperswithcode.com/method/yolov4
YOLOv4 Explained - Papers With Code
WEB12 rows · YOLOv4 is a one-stage object detection model that improves on YOLOv3 with …
- COMPONENT TYPE
  Cosine Annealing Learning Rate Schedules
  CSPDarknet53 Convolutional Neural Networks
  CutMix Image Data Augmentation
  DropBlock Regularization
  See all 12 rows on paperswithcode.com
Towards Data Science
https://towardsdatascience.com/yolo-v4-optimal...
YOLO v4: Optimal Speed & Accuracy for object detection
WEBMay 17, 2020 · YOLO v4 achieves state-of-the-art results (43.5% AP) for real-time object detection and is able to run at a speed of 65 FPS on a V100 GPU. If you want less …
- Estimated Reading Time: 9 mins
arXiv.org
https://arxiv.org/abs/2004.10934
Title: YOLOv4: Optimal Speed and Accuracy of Object Detection
WEBApr 23, 2020 · YOLOv4: Optimal Speed and Accuracy of Object Detection. There are a huge number of features which are said to improve Convolutional Neural Network (CNN) …
- Author: Alexey Bochkovskiy, Chien-Yao Wang, Hong-Yuan Mark Liao
- Cite as: arXiv:2004.10934 [cs.CV]
- Publish Year: 2020
Medium
https://medium.com/aiguys/yolo-v4-explai…
YOLO v4 explained in full detail | AIGuys - Medium
WEBDec 23, 2021 · Deep look into the YOLOv4 or YOLO-v4. Research paper review. Bag of freebies, Bag of specials, Backbone, neck, head, Object detector architecture.
Ultralytics YOLOv8 Docs
https://docs.ultralytics.com/models/yolov4
YOLOv4 - Ultralytics YOLO Docs
WEBNov 12, 2023 · YOLOv4 is a powerful and efficient object detection model that strikes a balance between speed and accuracy. Its use of unique features and bag of freebies …
PyImageSearch
https://pyimagesearch.com/2022/05/16…
Achieving Optimal Speed and Accuracy in Object …
WEBMay 16, 2022 · After running the YOLOv4 pre-trained COCO model on the below images, we learn that the model makes zero mistakes and perfectly detects the objects in all the images. Compared to YOLOv3, which …
arXiv.org
https://arxiv.org/pdf/2004.10934
[PDF]
YOLOv4: Optimal Speed and Accuracy of Object Detection
WEBWe develope an efficient and powerful object detection model. It makes everyone can use a 1080 Ti or 2080 Ti GPU to train a super fast and accurate object detector. We verify the …
Github
https://github.com/georgiosouzounis/o…
A complete guide to object detection using YOLO V4 …
WEBA complete guide to object detection using YOLO V4 and OpenCV. This collection of Google Colab-Notebooks demonstrates how to perform object detection using the YOLO V4 model. The material is seperated in two …
Towards Data Science
https://towardsdatascience.com/whats-new-in-yolov4-323364bb3ad3
What’s new in YOLOv4?. YOLO is a real-time object …
WEBMay 19, 2020 · YOLOv4 is twice as fast as EfficientDet (competitive recognition model) with comparable performance. In addition, AP (Average Precision) and FPS (Frames …
Roboflow
https://roboflow.com/model/yolov4
YOLOv4 Darknet Object Detection Model: What is, How to Use
WEBThe YOLO v4 repository is currently one of the best places to train a custom object detector, and the capabilities of the Darknet repository are vast. In this post, we discuss …
- Reviews: 1
MathWorks
https://www.mathworks.com/help/vision/ug/object...
Object Detection Using YOLO v4 Deep Learning - MathWorks
WEBCreate a YOLO v4 object detector by using the yolov4ObjectDetector function and train the detector using trainYOLOv4ObjectDetector function. This example also provides a …
Roboflow Blog
https://blog.roboflow.com/training-yolov4-on-a-custom-dataset
How to Train YOLOv4 on a Custom Dataset - Roboflow Blog
WEBMay 21, 2020 · We will take the following steps to implement YOLOv4 on our custom data: Introducing YOLO v4 versus prior object detection models. Configure our YOLOv4 GPU …
DataCamp
https://www.datacamp.com/blog/yolo-object-detection-explained
YOLO Object Detection Explained: A Beginner's Guide
WEBYou Only Look Once (YOLO) is a state-of-the-art, real-time object detection algorithm introduced in 2015 by Joseph Redmon, Santosh Divvala, Ross Girshick, and Ali Farhadi …
MathWorks
https://www.mathworks.com/help/vision/ug/getting...
Getting Started with YOLO v4 - MATLAB & Simulink - MathWorks
WEBThe YOLO v4 network outputs feature maps of sizes 19-by-19, 38-by-38, and 76-by-76 to predict the bounding boxes, classification scores, and objectness scores. Tiny YOLO v4 …
Roboflow Blog
https://blog.roboflow.com/yolov4-tactics
YOLOv4 - Ten Tactics to Build a Better Model - Roboflow Blog
WEBNov 13, 2020 · The YOLO v4 repository is currently one of the best places to train a custom object detector, and the capabilities of the Darknet repository are vast. In this post, we …
Github
https://github.com/RobotEdh/Yolov-4
RobotEdh/Yolov-4: Yolo v4 using TensorFlow 2.x - GitHub
WEBThe steps to use Yolo-V4 with TensorFlow 2.x are the following. 1. Build the TensorFlow model. The model is composed of 161 layers. Most of them are Conv2D, there are also 3 …
Medium
https://medium.com/analytics-vidhya/yolov4-vs...
YOLOv4 vs YOLOv4-tiny. Training custom YOLO detectors for …
WEBFeb 24, 2021 · For real-time object detection, YOLOv4-tiny is the better option when compared with YOLOv4 as faster inference time is more important than precision or …
Robocademy
https://robocademy.com/2020/05/01/a-g
A Gentle Introduction to YOLO v4 for Object detection in
WEBMay 1, 2020 · In this post, we are going to see the basics of object detection in the computer vision, basics of famous object detection system YOLO (You Only Look once), …
Github
https://github.com/matlab-deep-learning/pretrained-yolo-v4
matlab-deep-learning/pretrained-yolo-v4 - GitHub
WEBDetect Objects Using Pretrained YOLO v4. Use to code below to perform detection on an example image using the pretrained model. Note: This functionality requires Deep …
MathWorks
https://www.mathworks.com/help/deeplearning/ug/...
Object Detection Using YOLO v4 Deep Learning - MathWorks
WEBCreate a YOLO v4 object detector by using the yolov4ObjectDetector function and train the detector using trainYOLOv4ObjectDetector function. This example also provides a …
ScienceDirect
https://www.sciencedirect.com/science/article/pii/S0031320324007349
MSNet: Multi-Scale Network for Object Detection in Remote …
WEB2 days ago · Our model, when equipped with LGIFM, achieves a 73.7% mAP (3.5% ↑) as shown in Table 2 on DIOR dataset and reaches a 93.39% mAP (2.9% ↑) on HRRSD …
Roboflow
https://roboflow.com/model/yolov4-tiny
YOLOv4 Tiny Object Detection Model: What is, How to Use
WEBYOLOv4-tiny is the compressed version of YOLOv4 designed to train on machines that have less computing power. Its model weights are around 16 megabytes large, allowing …
- Reviews: 1
Springer
https://link.springer.com/article/10.1007/s10334-024-01203-5
Brain tumor detection and segmentation using deep learning
WEB3 days ago · Therefore, we selected three state-of-the-art deep learning-based detection networks i.e. Faster R-CNN, YOLO (version 4 &5) and SSD to investigate which …
MDPI
https://www.mdpi.com/2079-9292/13/17/3547
HRA-YOLO: An Effective Detection Model for Underwater Fish
WEBAug 10, 2024 · Deploying a high-precision, lightweight fish detection algorithm on underwater monitoring equipment with limited computational resources is a challenging …
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COMPONENT	TYPE
Cosine Annealing	Learning Rate Schedules
CSPDarknet53	Convolutional Neural Networks
CutMix	Image Data Augmentation
DropBlock	Regularization

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