Underground Defects Detection Based on GPR by Fusing Simple Linear Iterative Clustering Phash (SLIC-Phash) and Convolutional Block Attention Module (CBAM)-YOLOv8-Reference-Cited by-同舟云学术

Underground Defects Detection Based on GPR by Fusing Simple Linear Iterative Clustering Phash (SLIC-Phash) and Convolutional Block Attention Module (CBAM)-YOLOv8

Published:2024 Issue: Volume:12 Page:25888-25905
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Wang Niannian¹^ORCID,Zhang Zexi¹^ORCID,Hu Haobang¹^ORCID,Li Bin¹,Lei Jianwei¹^ORCID

Affiliation:

1. Yellow River Laboratory, Zhengzhou University, Zhengzhou, China

Funder

National Key Research and Development Program of China

National Natural Science Foundation of China

Program for Innovative Research Team (in Science and Technology) in University of Henan Province

Program for Science & Technology Innovation Talents in Universities of Henan Province

Postdoctoral Science Foundation of China

Key Scientific Research Projects of Higher Education in Henan Province

Open Fund of Changjiang Institute of Survey, Lanning, Design and Research

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/6287639/10380310/10436091.pdf?arnumber=10436091

Reference46 articles.

1. Surface and borehole ground-penetrating-radar developments

2. GPR surveys for the prevention of karst risk in underground gypsum quarries

3. Vibration-based monitoring of civil infrastructure: challenges and successes

4. GPR B scan image analysis with deep learning methods

5. MEML: A Deep Data Augmentation Method by Mean Extrapolation in Middle Layers

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