Andreas Stamkos

Technological Educational Institute of Eastern Macedonia and Thrace

Papers

Total Citations

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About

Andreas Stamkos is a researcher at the forefront of applying artificial intelligence to industrial materials inspection, with a specialized focus on marble surface analysis. His work bridges the gap between traditional manufacturing quality control and modern deep learning techniques, addressing critical challenges in automated defect detection. Stamkos’s most impactful contribution, “Towards Robotic Marble Resin Application: Crack Detection on Marble Using Deep Learning” (2022), has garnered 20 citations and demonstrates how machine vision can overcome the limitations of manual inspection, which is both time-consuming and error-prone. This foundational work explores the decades-old challenge of using computer vision for defect detection in production lines, specifically adapting these methods for the unique properties of marble surfaces. More recently, Stamkos has ventured into generative AI, as evidenced by his 2025 paper “Utilizing generative AI for crack detection in the marble industry,” which tackles the persistent problem of limited annotated datasets in niche industrial applications. By proposing innovative solutions for data augmentation and synthetic training data, Stamkos is pushing the boundaries of what’s possible in automated quality assurance. His research not only advances the field of industrial computer vision but also has practical implications for reducing waste and improving efficiency in stone processing industries.