The classification method is based on the use of supervised machine learning algorithms, assisted by surveyors' strategies and expertise to identify defective individual masonry units, through to broader global patterns for groups of stones. The proposed approach has been tested on the main facade of...
An integrated visual defect detection and classification system. The invention includes adaptive defect detection and image labeling, defect feature measures, and a knowledge based inference shell/engine for classification based on fuzzy logic. The combination of these elements comprises a method and syste...
AUTOMATED DEFECT CLASSIFICATION 专利名称：AUTOMATED DEFECT CLASSIFICATION 发明人：Corville O. Allen,Albert A. Chung,Binh C.Truong,Kam K. Yee 申请号：US11945421 申请日：20071127 公开号：US20090138851A1 公开日：20090528 专利内容由知识产权出版社提供 专利附图：摘要：Embodiments of the present invention ...
Electron microscopy and defect analysis are a cornerstone of materials science, as they offer detailed insights on the microstructure and performance of a wide range of materials and material systems. Building a robust and flexible platform for automated defect recognition and classification in electron ...
aThe ROI A-scan signals are passed through the automated signal classification system and identified as belonging to defect or clean class. If the scanned ROI belongs to a defect of interest, the second step of the approach is to characterize the ROI with a C-scan imaging process for depth ...
classification, artifact detection, FIR filtering, wavelet analysis, statistical analysis, pattern recognition techniques, or the like, to evaluate image quality parameters and/or identify defects in the image(s). A typical banding defect analysis of the image data will provide data such as the foll...
3). Due to these minuscule differences, the classification here had to be made on the second derivative of spectra. Nevertheless, only a weak classifier could be established, which is able to form a ratio from MSI-H or MSS assigned spectra. More precisely, the classifier always detects a ...
The dis- criminator which is a binary classifier operator predicts whether an image is false or real when the input image passes through the four blocks. The discriminator mis- takes the generated sample image for a real image only if the real and generated images are close. The discriminator...
To ensure interpretability, we identified locations in the scan that contributed most to the classification using CAMs. We have implemented the Class Activation Mapping based on the descriptions from Zhou et al.50 Briefly, the authors used a trained CNN classifier to localize the input image by us...
Neovascular age-related macular degeneration (nAMD) is one of the major causes of irreversible blindness and is characterized by accumulations of different lesions inside the retina. AMD biomarkers enable experts to grade the AMD and could be used for th