Defect detection in material micro-images has a significant impact on the study of the relationship between the micro-structure and macro-properties, however, material microdefects are usually ...

This model is trained using the above dataset and is then used to classify new images with an accuracy of roughly 94%. This work also proposes a detect classification method which can identify the ...

Silicon wafer is the raw material of semiconductor chip. It is important and challenging to research a fast and accurate method of identifying and classifying wafer structural defects. To this end, we ...

Run example notebooks in Google Colab: Make predictions of image F1 score with Random forest model and object predictions with Mask R-CNN using final model fit to all data. This model was trained on ...

However, conventional methods rely on heavy computational processing and image enhancement and may not truly reflect subtle defects, particularly in low-light settings. advertisement Tech Xplore ...

Researchers have designed a robust image-based anomaly detection (AD) framework with illumination enhancement and noise suppression features that can enhance the detection of subtle defects in low ...