Scinovex
Physical Sciences → Engineering → Industrial and Manufacturing Engineering

Industrial Vision Systems and Defect Detection

This cluster of papers focuses on the application of machine vision, texture analysis, and deep learning techniques for the automated detection and classification of fabric defects in industrial settings, particularly in semiconductor manufacturing. The research covers various methods such as Gabor filters, wafer map defect classification, and virtual metrology to enhance the accuracy and efficiency of fabric defect detection systems.

102.1K works worldwide735.8K citations
Fabric Defect DetectionMachine VisionTexture AnalysisSemiconductor ManufacturingDeep LearningWafer Map Defect ClassificationGabor FiltersAutomated InspectionSurface Defect DetectionVirtual Metrology

Journals publishing in this area

1
Applied Sciences
ISSN 2076-3417971 articles in this topic
215h-index
2
197h-index
3IEEE Transactions on Instrumentation and Measurement cover
IEEE Transactions on Instrumentation and Measurement
ISSN 0018-9456834 articles in this topic
195h-index
4IEEE Transactions on Image Processing cover
IEEE Transactions on Image Processing
ISSN 1057-7149634 articles in this topic
391h-index
5International Journal of Production Research cover
International Journal of Production Research
ISSN 0020-7543359 articles in this topic
249h-index
6IEEE Transactions on Industrial Informatics cover
IEEE Transactions on Industrial Informatics
ISSN 1551-3203338 articles in this topic
252h-index