An Efficient Explainable Convolutional Network with Visualization of Feature Maps for Enhanced Understanding of Building Facade Defects-Reference-Cited by-同舟云学术

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An Efficient Explainable Convolutional Network with Visualization of Feature Maps for Enhanced Understanding of Building Facade Defects

Published:2024-09 Issue:5 Volume:38 Page:
ISSN:0887-3801
Container-title:Journal of Computing in Civil Engineering
language:en
Short-container-title:J. Comput. Civ. Eng.

Author:

Shin Hyunkyu¹,Lee Sanghyo²

Affiliation:

1. Assistant Professor, Div. of Architecture, Mokwon Univ., Daejeon 35349, Republic of Korea.

2. Associate Professor, Div. of Smart Convergence Engineering, Hanyang Univ. Education Research Industry Cluster at Ansan, Ansan 15588, Republic of Korea (corresponding author).

Publisher

American Society of Civil Engineers (ASCE)

Link

https://ascelibrary.org/doi/pdf/10.1061/JCCEE5.CPENG-5857

Reference53 articles.

1. Robust Pixel-Level Crack Detection Using Deep Fully Convolutional Neural Networks

2. A deep‐learning‐based computer vision solution for construction vehicle detection

3. Evaluation of deep learning approaches based on convolutional neural networks for corrosion detection

4. Encoder–decoder network for pixel‐level road crack detection in black‐box images

5. Autonomous Structural Visual Inspection Using Region-Based Deep Learning for Detecting Multiple Damage Types

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