Lightweight pothole detection method based on improved YOLOv5

Author:

Zou Yang1,Wan Jiangcheng1,Wang Binjie1

Affiliation:

1. Chongqing University of Posts and Telecommunications,School of Computer Science and Technology,Chongqing,China,400065

Publisher

IEEE

Reference18 articles.

1. Nuts&bolts: YOLO-v5 and image processing based component identification system

2. Yolov4: Optimal speed and accuracy of object detection[J];bochkovskiy;arXiv preprint arXiv 2004 10934,2020

3. SimAM: A simple, parameter-free attention module for convolutional neural networks[C];yang;International Conference on Machine Learning,2021

4. Annotated Potholes Image Dataset;rahman,2020

5. Application of Various YOLO Models for Computer Vision-Based Real-Time Pothole Detection

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1. Real Time Implementation of Pothole Detection Using Deep Learning;2024 2nd International Conference on Networking and Communications (ICNWC);2024-04-02

2. Enhanced Pothole Detection in Road Condition Assessment Using YOLOv8;2024 IEEE International Conference for Women in Innovation, Technology & Entrepreneurship (ICWITE);2024-02-16

3. YOLOv7-SIMAM: An effective method for SAR ship detection;2024 4th International Conference on Neural Networks, Information and Communication (NNICE);2024-01-19

4. Real-Time Multi-Scale Pothole Detection using Transformer;2023 International Conference on Frontiers of Information Technology (FIT);2023-12-11

5. Pothole Detection Using Deep Learning;2023 2nd International Conference on Futuristic Technologies (INCOFT);2023-11-24

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