Jorge Silva
Papers
1
Total Citations
6
H-Index
1
About
Jorge Silva is a researcher at the forefront of applying artificial intelligence to textile manufacturing, with a particular focus on quality inspection and process automation. His work centers on computer vision technology for textile analysis, especially in the detection and measurement of fabric hairiness—a critical quality parameter for pile fabric products. Silva’s most cited paper, “Fabric Hairiness Analysis for Quality Inspection of Pile Fabric Products Using Computer Vision Technology” (2022, 6 citations), addresses a longstanding challenge in the textile industry: the transition from manual, subjective inspection to automated, objective quality control. By developing AI-driven computer vision systems, Silva demonstrates how deep learning can replace human visual inspection, improving both accuracy and throughput in manufacturing environments. His research contributes to the broader Industry 4.0 movement, showing how traditional sectors like textiles can leverage artificial intelligence to enhance productivity and product consistency. Silva’s work is particularly notable for its practical, application-oriented approach—bridging the gap between computer vision algorithms and real-world manufacturing constraints. For students and researchers interested in industrial AI, textile engineering, or applied computer vision, Silva’s research offers a compelling case study in how machine learning can transform legacy industries through intelligent automation.
Research Focus
Key Achievements
Top Papers
- 1