A5101554662- Surface Roughness and Optical Measurements
- Infrared Target Detection Methodologies
- Industrial Vision Systems and Defect Detection
- Infrastructure Maintenance and Monitoring
- Thermography and Photoacoustic Techniques
- Infrared Thermography in Medicine
- Advanced Image Fusion Techniques
- Non-Destructive Testing Techniques
- Advanced SAR Imaging Techniques
- Medical Image Segmentation Techniques
- Advanced Image and Video Retrieval Techniques
- Manufacturing Process and Optimization
- Image Enhancement Techniques
- Image Retrieval and Classification Techniques
- Ultrasonics and Acoustic Wave Propagation
- Photoacoustic and Ultrasonic Imaging
- Optical Polarization and Ellipsometry
Nanjing University of Aeronautics and Astronautics
2020-2023
Ministry of Industry and Information Technology
2021-2022
Surface defects have an adverse effect on the quality of industrial products, and vision-based defect detection is widely researched due to its objective stable performance. However, task still challenging diversified types complex background texture. The robust principal component analysis (RPCA) has proven applicable in inspection by regarding nondefective as low-rank part defective area sparse part. such methods cannot sufficiently detect cluttered background, noise interference, limited...
For infrared (IR) small target detection, we propose a new spatial-temporal tensor (STT) decomposition model based on the Schatten capped <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$p$ </tex-math></inline-formula> norm (TSC notation="LaTeX">$p\text{N}$ ) and total variation (TV) regularization. First, to explore spatial temporal information, construct an STT introduce prior weight map. Then, replacing...
The restoration of nonuniform distorted infrared (IR) images is crucial for human visual perception and subsequent application tasks. However, existing methods sometimes fail to yield visually natural decompositions perform insufficiently in the preservation meaningful structures while suppressing disturbing noise. A spatially adaptive hybrid ℓ1 − ℓ2 variational framework intensity correction IR proposed. Considering piecewise constant characteristics latent images, a weighted ℓ1-norm...
Surface defect detection is an extremely crucial step to ensure the quality of industrial products. Nowadays, convolutional neural networks (CNNs) based on encoder-decoder architecture have achieved tremendous success in various tasks. However, due intrinsic locality convolution, they commonly exhibit a limitation explicitly modeling long-range interactions, critical for pixel-wise complex cases, e.g., cluttered background and illegible pseudo-defects. Recent transformers are especially...