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YOLOv4: Optimal Speed and Accuracy of Object Detection
- Author: Alexey Bochkovskiy, Chien-Yao Wang, Hong-Yuan Mark Liao
- Cite as: arXiv:2004.10934 [cs.CV]
- Publish Year: 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) accuracy. Practical testing of combinations of such features on large datasets, and theoretical justification of the result, is required.WongKinYiu/PyTorch_YOLOv4 - GitHub
- This is PyTorch implementation of YOLOv4 which is based on ultralytics/yolov3.
•[original Darknet implementation of YOLOv4] - •[ultralytics/yolov5 based PyTorch implementation of YOLOv4].
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- This is PyTorch implementation of YOLOv4 which is based on ultralytics/yolov3.
What is YOLOv4? A Detailed Breakdown. - Roboflow Blog
YOLOv4 Explained - Papers With Code
WEB12 rows · YOLOv4 is a one-stage object detection model that improves on YOLOv3 with …
YOLOv4 - Ultralytics YOLO Docs
WEBNov 12, 2023 · Learn about YOLOv4, a real-time object detection model launched in 2020 by Alexey Bochkovskiy. Find out its architecture, features, performance, and usage …
WEBA paper that introduces YOLOv4, a fast and accurate object detection model that runs on a single GPU. It compares YOLOv4 with other state-of-the-art models and explains its …
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YOLOv4: Optimal Speed and Accuracy of Object …
WEBApr 23, 2020 · TLDR. This work uses new features: WRC, CSP, CmBN, SAT, Mish activation, Mosaic data augmentation, C mBN, DropBlock regularization, and CIoU loss, and combine some of them to achieve …
YOLOv4: Optimal Speed and Accuracy of Object …
WEBWe use new features: WRC, CSP, CmBN, SAT, Mish activation, Mosaic data augmentation, CmBN, DropBlock regularization, and CIoU loss, and combine some of them to achieve state-of-the-art results: 43.5% AP …
[2004.10934] YOLOv4: Optimal Speed and Accuracy of Object …
WEBApr 23, 2020 · A paper that presents a new object detection model based on Convolutional Neural Networks and various features. It claims to achieve state-of-the-art results on MS …
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 …
Achieving Optimal Speed and Accuracy in Object …
WEBMay 16, 2022 · Learn how to build and train a fast and accurate object detection network based on YOLOv4, a state-of-the-art model that combines various novel techniques. Explore the components, data …
YOLO v4 explained in full detail | AIGuys - Medium
WEBDec 23, 2021 · YOLOv4 is very complex and that’s why this blog is to understand the advancement made over the original YOLO. So, without further ado let’s unwrap …
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 …
YOLOv4 in the CLOUD: Install and Run Object Detector (FREE …
WEBMay 20, 2020 · Learn how to get YOLOv4 Object Detection running in the Cloud with Google Colab. YOLOv4 is brand new and boasts many performance and speed …
YOLO Object Detection Explained: A Beginner's Guide
WEBYOLOv4 — Optimal Speed and Accuracy of Object Detection. This version of YOLO has an Optimal Speed and Accuracy of Object Detection compared to all the previous versions …
AlexeyAB/darknet: YOLOv4 / Scaled-YOLOv4 / YOLO - GitHub
WEBYOLOv7 surpasses all known object detectors in both speed and accuracy in the range from 5 FPS to 160 FPS and has the highest accuracy 56.8% AP among all known real …
WEBSORT, and YOLOv4 and Deep SORT produced the best overall counting percentage for all vehicles. Index Terms—Deep learning, Object Detection, Tracking, Vehicle Counts I. …
Review — YOLOv4: Optimal Speed and Accuracy of Object …
WEBAug 14, 2021 · As seen above, with different types of GPU, YOLOv4 are located on the Pareto optimality curve and are superior to the fastest and most accurate detectors in …
ultralytics/docs/en/models/yolov4.md at main - GitHub
WEBYOLOv4, which stands for "You Only Look Once version 4," is a state-of-the-art real-time object detection model developed by Alexey Bochkovskiy in 2020. It achieves an …
Modeling of SPM-GRU ping-pong ball trajectory prediction …
WEB2 days ago · In contrast, YOLOv4-Tiny, a lightweight model, shows relatively weak performance on these categories with an average accuracy of only 64.38%. However, …
GitHub - Tianxiaomo/pytorch-YOLOv4: PyTorch ,ONNX and …
WEBRun the following command to convert YOLOv4 ONNX model into TensorRT engine. trtexec --onnx= <onnx_file> --explicitBatch --saveEngine= <tensorRT_engine_file> - …
Autonomous Mosquito Habitat Detection Using Satellite Imagery …
WEBMar 8, 2022 · To improve the grasp quality, we propose a robotic arm grasping system using YOLOv4 combined with a particle filter (PF) algorithm, which can be applied in a …
Object Detection and Tracking Algorithms for Vehicle ... - Springer
WEBNov 17, 2020 · YOLOv4. You Only Look Once (YOLO) is the state-of-the-art object detection algorithm. Unlike traditional object detection systems, YOLO investigates the …
HRA-YOLO: An Effective Detection Model for Underwater Fish
WEBAug 10, 2024 · To solve this problem, Zhang et al. built a YOLOv4-based method, which combines MobileNet v2 and depthwise separable convolutions to reduce the parameter …
Object Detection and Tracking Algorithms for Vehicle Counting: A ...
WEBJul 31, 2020 · Experimental results demonstrate that the combination of CenterNet and Deep SORT, Detectron2 and Deep SORT, and YOLOv4 and Deep SORT produced the …
目标检测-YOLOv4 - CSDN博客
WEB2 days ago · 文章浏览阅读289次，点赞11次，收藏7次。yolov4 是 yolo 系列的第四个版本，继承了 yolov3 的高效性，并通过大量优化和改进，在目标检测任务中实现了更高的精 …
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