A5041721642- Advanced Neural Network Applications
- Industrial Vision Systems and Defect Detection
- Non-Destructive Testing Techniques
- Advanced X-ray and CT Imaging
- Lung Cancer Treatments and Mutations
- Advanced Breast Cancer Therapies
- Cancer Immunotherapy and Biomarkers
- Image and Object Detection Techniques
Sun Yat-sen University
2024-2025
In the testing of chips, defect diagnostics in X-ray images packaging chips is mainly performed by humans, which time-consuming and inefficient. To overcome abovementioned problems, a novel intelligent system based on hybrid deep learning for chip was proposed. The consists four successive stages: image segmentation normalization, reconstruction detection, contour matching, qualification diagnosis. first stage used to localize external contours target remove extraneous backgrounds through...
As a non-destructive detection method, X-rays are widely used in the field of electronic component inspection. However, subsequent defect needs to be completed manually, which leads poor efficiency and low reliability due large number components. To solve above problems, we propose X-ray image method based on deep learning. On one hand, have designed an algorithm for segmentation correction images. other case fewer samples variable forms, only use defect-free training. We unsupervised...