Computer Vision for Construction Progress Monitoring: A Real-Time Object Detection Approach

no code implementations • 24 May 2023 • Jiesheng Yang, Andreas Wilde, Karsten Menzel, Md Zubair Sheikh, Boris Kuznetsov

Construction progress monitoring (CPM) is essential for effective project management, ensuring on-time and on-budget delivery.

Decision Making Management +2

A comparative study of attention mechanism and generative adversarial network in facade damage segmentation

no code implementations • 27 Sep 2022 • Fangzheng Lin, Jiesheng Yang, Jiangpeng Shu, Raimar J. Scherer

Attention mechanism and generative adversarial networks are two of the most popular strategies to improve the quality of semantic segmentation.

Generative Adversarial Network Segmentation +1

Fast Crack Detection Using Convolutional Neural Network

no code implementations • 23 May 2021 • Jiesheng Yang, Fangzheng Lin, Yusheng Xiang, Peter Katranuschkov, Raimar J. Scherer

To improve the efficiency and reduce the labour cost of the renovation process, this study presents a lightweight Convolutional Neural Network (CNN)-based architecture to extract crack-like features, such as cracks and joints.

Transfer Learning

Crack Semantic Segmentation using the U-Net with Full Attention Strategy

no code implementations • 29 Apr 2021 • Fangzheng Lin, Jiesheng Yang, Jiangpeng Shu, Raimar J. Scherer

Along with the rapid progress of deep learning technology, image semantic segmentation, an active research field, offers another solution, which is more effective and intelligent, to crack detection Through numerous artificial neural networks have been developed to address the preceding issue, corresponding explorations are never stopped improving the quality of crack detection.

Segmentation Semantic Segmentation