Sotiris A. Vassou
Papers
1
Total Citations
6
H-Index
1
About
Sotiris A. Vassou is a researcher specializing in computer vision and image retrieval, with a particular focus on developing efficient, invariant descriptors for visual content analysis. His most cited work, "CoMo: a scale and rotation invariant compact composite moment-based descriptor for image retrieval" (2018, 6 citations), introduces a novel descriptor that combines multiple moment-based features to achieve robustness against geometric transformations while maintaining a compact representation. This contribution addresses a critical challenge in content-based image retrieval—balancing invariance with computational efficiency—and has been cited by peers working on feature extraction and multimedia indexing. Vassou’s research bridges theoretical advances in moment invariants with practical applications in large-scale image databases. While his citation count reflects an early-career stage, the CoMo descriptor stands as a notable achievement for its innovative synthesis of existing moment theories into a unified, high-performance framework. His work is particularly relevant for students and researchers exploring scalable, transformation-invariant methods in computer vision, offering a solid foundation for further developments in visual search and pattern recognition.
Research Focus
Key Achievements
Top Papers
- 1