Papers

2

Total Citations

22

H-Index

2

About

Vassilis Kalpakis is a researcher at the forefront of applying artificial intelligence to industrial automation, with a primary focus on defect detection in natural stone materials. His work centers on the intersection of computer vision, deep learning, and robotics, specifically targeting the marble industry’s need for automated quality control. Kalpakis’s major contribution lies in developing deep learning models capable of identifying cracks on marble surfaces—a task traditionally performed through manual inspection, which is both time-consuming and error-prone. His most cited work, "Towards Robotic Marble Resin Application: Crack Detection on Marble Using Deep Learning" (2022), has garnered 20 citations and establishes a foundational approach for integrating machine vision into production lines. More recently, Kalpakis has explored the potential of generative AI to address the challenge of limited annotated datasets in this domain, as demonstrated in his 2025 publication. By tackling the scarcity of training data, his research paves the way for more robust and scalable inspection systems. Kalpakis’s work is particularly notable for bridging the gap between cutting-edge AI techniques and practical industrial applications, offering a pathway toward fully automated, robotic marble processing.

Research Focus

Key Achievements

2
H-Index
2
Papers
22
Total Citations
11
Avg Citations/Paper
🏆 Most Cited Paper
Towards Robotic Marble Resin Application: Crack Detection on Marble Using Deep Learning
20 citations · 2022
📈 Most Prolific Year: 2022 (1 Papers)
🤝 Key Collaborators: 8
🏛 Institutions: Technological Educational Institute of Eastern Macedonia and Thrace

Top Papers

  1. 1
  2. 2

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago