Efficient Pavement Crack Detection in Drone Images using Deep Neural Networks-Reference-Cited by-同舟云学术

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Efficient Pavement Crack Detection in Drone Images using Deep Neural Networks

Published:2023-02-05 Issue: Volume: Page:
ISSN:
Container-title:2023 International Conference on Electronics, Information, and Communication (ICEIC)
language:
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Author:

Kim Heegwang¹,Sung Junghoon¹,Kim Mingi²,Park Chanyeong¹,Paik Joonki¹

Affiliation:

1. Chung-Ang University,Image Processing and Intelligent System Laboratory Graduate School of Advanced Imaging Science, Multimedia, and Film,Seoul,Korea

2. Chung-Ang University,Image Processing and Intelligent System Laboratory Graduate School of Artificial Intelligence,Seoul,Korea

Funder

Defense Acquisition Program Administration

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10049840/10049805/10049911.pdf?arnumber=10049911

Reference7 articles.

1. High-resolution processing and sigmoid fusion modules for efficient detection of small objects in an embedded system

2. Crack Segmentation Network using Tversky Loss Function with Variable Alpha and Beta

3. AggCrack: An Aggregated Attention Model for Robotic Crack Detection in Challenging Airport Runway Environment

4. Yolox: Exceeding yolo series in 2021;ge,2021

5. RDD2022: A multi-national image dataset for automatic Road Damage Detection;arya,2022

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