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Title: 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.org[2004.10934] YOLOv4: O…
YOLOv4: Optimal Speed and Accuracy of Object Detection. There are a huge …
arXiv:2209.02976v1 [cs.CV] …
lowing YOLOv4 and YOLOv5. We enhance the neck with RepBlocks or …
arXiv.org e-Print archive
Explore a wide range of e-prints on the arXiv.org archive, including papers on …
YOLOv4: Optimal Speed …
Figure 1: Comparison of the proposed YOLOv4 and other state-of-the-art …
- 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 …
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 …
WEBFigure 1: Comparison of the proposed YOLOv4 and other state-of-the-art object detectors. YOLOv4 runs twice faster than EfficientDet with comparable performance. Improves …
WEBAdditionally, PDF files can be easily annotated, bookmarked, and searched for specific terms, making them highly practical for studying or referencing. When it comes to …
[2004.10934] YOLOv4: Optimal Speed and Accuracy of Object …
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) …
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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 …
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 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. …
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 optimal …
YOLOv4: Optimal Speed and Accuracy of Object …
WEBIn this research, we designed an automated drone detection system using YOLOv4. The model was trained using drone and bird datasets. We then evaluated the trained YOLOv4 model on the testing dataset, using mean …
(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. …
Achieving Optimal Speed and Accuracy in Object Detection …
WEBMay 16, 2022 · To learn the novel techniques used and various experiments performed to build a practical YOLOv4 object detector that is fast and accurate and run an inference …
YOLO-OBJECT-DETECTION-TUTORIALS/YoloV4.pdf at main
WEBYoloV4.pdf. Cannot retrieve latest commit at this time. History. 7.88 MB. Contribute to MLForNerds/YOLO-OBJECT-DETECTION-TUTORIALS development by creating an …
WEBAbstract. Research on deep learning has always had two main streams: (1) design a powerful network architecture and train it with existing learning methods to achieve the …
WEBYOLO has become a central real-time object detection system for robotics, driverless cars, and video monitoring applications. We present a comprehensive analysis of YOLO’s …
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 …
ABYOLOv4: improved YOLOv4 human object detection based on …
WEBJan 4, 2024 · YOLOv4 consists of three main components: the backbone network (CSPDarkNet53) for feature extraction, the Spatial Pyramid Pooling (SPP) module to …
(PDF) YOLOv3 and YOLOv4: Multiple Object Detection for …
WEBAug 1, 2020 · The results indicate that Faster RCNN beats YOLOv3 and YOLOV4 in car detection with low error detection, whereas YOLOv3 and YOLOv4 outperform near-miss …
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 …
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 …
WEBDec 15, 2018 · YOLOv4 is well with its AP and FPS improvements. On a single CPU, YOLOv4 optimizes real-time object detection and training. On the COCO dataset, …
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.
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