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YOLOv4: Optimal Speed and Accuracy of Object Detection
WEBApr 23, 2020 · View a PDF of the paper titled YOLOv4: Optimal Speed and Accuracy of Object Detection, by Alexey Bochkovskiy and 2 other authors. There are a huge number …
- Author: Alexey Bochkovskiy, Chien-Yao Wang, Hong-Yuan Mark Liao
- Cite as: arXiv:2004.10934 [cs.CV]
- Publish Year: 2020
See results only from arxiv.orgarXiv.org e-Print archive
Explore a wide range of e-prints on the arXiv.org archive, including papers on …
YOLOv4: Optimal Speed an…
YOLOv4 runs twice faster than EfficientDet with comparable performance. Improves …
- Bag of Freebies (BoF) for backbone: CutMix and Mosaic data augmentation, DropBlock regularization, Class label smoothing Bag of Specials (BoS) for backbone: Mish activa-tion, Cross-stage partial connections (CSP), Multi-input weighted residual connections (MiWRC) Bag of Freebies (BoF) for detector: CIoU-loss, CmBN, DropBlock regularization, Mosaic ...
- Author: Alexey Bochkovskiy, Chien-Yao Wang, Hong-Yuan Mark Liao
- Publish Year: 2020
YOLOv4: Optimal Speed and Accuracy of Object …
WEBTLDR. 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 state-of-the-art …
- Studies of pp yolov4 pdf
[2004.10934] YOLOv4: Optimal Speed and Accuracy of Object …
WEBApr 23, 2020 · A paper that presents a new object detection model, YOLOv4, with various features and techniques to improve CNN accuracy and speed. The paper is not in PDF …
WEBper are conducted based on PaddlePaddle, we call it PP-YOLO. By combining multiple tricks, PP-YOLO can achieve a better balance between effectiveness (45.2% mAP) and …
WEBImproves YOLOv3’s AP and FPS by 10% and 12%, respectively. The main goal of this work is designing a fast operating speed of an object detector in production systems and opti …
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YOLOv4: Optimal Speed and Accuracy of Object Detection
WEBYOLOv4: Optimal Speed and Accuracy of Object Detection. There are a huge number of features which are said to improve Convolutional Neural Network (CNN) accuracy. …
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 …
YOLOv4: Optimal Speed and Accuracy of Object …
WEBThe aim of this paper is to improve the newly released, YOLOv4 detector, specifically, for vehicle tracking applications using some existing methods such as optimising anchor box predictions by using k-means clustering.
[2004.10934] YOLOv4: Optimal Speed and Accuracy …
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 …
[PDF] PP-YOLO: An Effective and Efficient …
WEBA new enhanced YOLOv4-based model is proposed that outperforms the accuracy of YOLov4 without considerably compromising its speed and several optimization techniques are explored, mainly grouped, depth …
WEBlowing YOLOv4 and YOLOv5. We enhance the neck with RepBlocks or CSPStackRep Blocks to have Rep-PAN. Head: We simplify the decoupled head to make it more …
WEBWe show that the YOLOv4 object detection neural net-work based on the CSP approach, scales both up and down and is applicable to small and large networks while main …
(PDF) YOLOv4: Optimal Speed and Accuracy of Object Detection …
WEBApr 22, 2020 · Comparison of the proposed YOLOv4 and other state-of-the-art object detectors. YOLOv4 runs twice faster than EfficientDet with comparable performance. …
(PDF) Scaled-YOLOv4: Scaling Cross Stage Partial Network
WEBPDF | On Jun 1, 2021, Chien-Yao Wang and others published Scaled-YOLOv4: Scaling Cross Stage Partial Network | Find, read and cite all the research you need on …
(PDF) PP-YOLO: An Effective and Efficient Implementation
WEBJul 23, 2020 · By combining multiple tricks, PP-YOLO can achieve a better balance between effectiveness (45.% mAP) and efficiency (72.9 FPS), surpassing the existing …
PP-YOLO Surpasses YOLOv4 - State of the Art Object Detection …
WEBAug 3, 2020 · PP-YOLO Surpasses YOLOv4 - State of the Art Object Detection Techniques. Baidu publishes PP-YOLO and pushes the state of the art in object …
WEBThis paper proposes a model scaling method based on YOLOv4, a state-of-the-art object detection network. The method can scale up and down the network size, depth, width, …
PP-YOLO: An Effective and Efficient Implementation of Object …
WEBJul 23, 2020 · By combining multiple tricks, PP-YOLO can achieve a better balance between effectiveness (45.2% mAP) and efficiency (72.9 FPS), surpassing the existing …
(PDF) YOLOv4‐dense: A smaller and faster YOLOv4 for …
WEBNov 8, 2022 · Experimental results on NVIDIA JETSON TX2 embedded platform demonstrate that YOLOv4‐dense can achieve a higher accuracy, faster speed with …
arXiv.org e-Print archive
WEBExplore a wide range of e-prints on the arXiv.org archive, including papers on YOLO object detection and its various architectures.
(PDF) PP-YOLOv2: A Practical Object Detector - ResearchGate
WEBApr 21, 2021 · This paper will analyze a collection of refinements and empirically evaluate their impact on the final model performance through incremental ablation study. Things …
[2011.08036] Scaled-YOLOv4: Scaling Cross Stage Partial …
WEBNov 16, 2020 · View a PDF of the paper titled Scaled-YOLOv4: Scaling Cross Stage Partial Network, by Chien-Yao Wang and 2 other authors. We show that the YOLOv4 object …
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