Concrete structures like roads and bridges require nondestructive testing methods to identify interior defects without destroying their structure. Most methods send sound waves into the material and ...
Across the physical world, many intricate structures form via symmetry breaking. When a system with inherent symmetry ...
The dataset is already organized in YOLO format in the steel_dataset/ directory. If you need to reorganize from original format, see utility/reorganize_dataset.py. steel-defect-detection/ ├── ...
The European Space Agency (ESA) is accelerating a quiet revolution on the factory floor: using artificial intelligence to design, inspect, ...
Abstract: Insulator defect detection is essential for maintaining reliable power delivery systems. Recently, insulator image detection has emerged as a promising alternative to traditional manual ...
1 Guangzhou Institute of Metrology and Testing Technology, Guangzhou, China 2 School of Artificial Intelligence and Automation, Huazhong University of Science and Technology, Wuhan, China Introduction ...
Researchers from Stony Brook University, in collaboration with Ecosuite and Ecogy Energy, have developed a self-supervised machine-learning algorithm designed to identify physical anomalies in solar ...
Introduction: Accurate defect detection in dissimilar metal welds (DMWs) remains a major challenge due to heterogeneous microstructures and imaging noise. Methods: In this study, we propose a novel ...
A new technical paper titled “DECOR: Deep Embedding Clustering with Orientation Robustness” was published by researchers at Oregon State University and Micron Technology. “In semiconductor ...
This project code is forked from https://github.com/DetectionTeamUCAS/FPN_Tensorflow. I have only made minor changes on this wonderful and clear project. Thanks for ...
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