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Pairing human and machine-vision in industrial inspection tasks
C. Sylla
MT School of Management
Research output
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Contribution to journal
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Article
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peer-review
4
Scopus citations
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Dive into the research topics of 'Pairing human and machine-vision in industrial inspection tasks'. Together they form a unique fingerprint.
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Keyphrases
Industrial Inspection
100%
Computer Vision
100%
Human Vision
100%
Inspection Task
100%
System Performance
50%
Error-prone
50%
Quality Control
50%
Machine Vision Inspection
50%
Enhanced System
50%
Defect Detection
50%
Positive Attributes
50%
Detection Performance
50%
Type I Error
50%
Type II Error
50%
Signal Detector
50%
Inspection System
50%
Vision Inspection System
50%
Rate Effect
50%
Vision Devices
50%
Fault Rate
50%
Quality Characteristics
50%
Item Type
50%
Outgoing Quality
50%
Engineering
Systems Performance
100%
Tasks
100%
Quality Control
100%
Detection Performance
100%
Defect Detection
100%
Quality Characteristic
100%
Computer Science
Machine Vision
100%
Inspection System
66%
Systems Performance
33%
Detection Performance
33%
Quality Characteristic
33%
Successive Stage
33%
Agricultural and Biological Sciences
Detectors
100%
Quality Control
100%
Nursing and Health Professions
Quality Control
100%