Ioannis Tsimperidis

International Hellenic University, Democritus University of Thrace

Papers

Total Citations

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About

Ioannis Tsimperidis is a researcher at the forefront of applying artificial intelligence and computer vision to industrial automation, with a particular focus on the marble and stone industry. His primary research areas include deep learning-based defect detection, generative AI, and robotic vision systems for quality control in manufacturing. Tsimperidis’s major contribution lies in developing automated crack detection methodologies that replace slow, error-prone manual inspection. His most cited work, "Towards Robotic Marble Resin Application: Crack Detection on Marble Using Deep Learning" (2022), has garnered 20 citations and demonstrates how machine vision can accurately identify surface cracks on marble, paving the way for robotic repair applications. More recently, his 2025 paper "Utilizing generative AI for crack detection in the marble industry" tackles the critical challenge of limited annotated datasets by exploring synthetic data generation—a novel approach that could significantly advance defect detection in niche industrial settings. Through these efforts, Tsimperidis is helping to modernize traditional stoneworking industries, reducing waste and improving product quality. His work sits at the intersection of computer vision, robotics, and materials science, offering practical solutions that bridge cutting-edge AI research with real-world manufacturing challenges.