Research area
Pattern Recognition
Detecting structure, regularities, and meaning in complex data through statistical and learning-based methods.
Overview
Pattern Recognition
Detecting structure, regularities, and meaning in complex data through statistical and learning-based methods.
Areas of interest
01Statistical pattern recognition
02Feature extraction
03Classification
04Clustering
05Anomaly detection
06Sequence and time-series patterns
07Representation learning
08Model evaluation
Projects in this area
All projects →Projects in this area will appear here as they are published.
Recent publications across DRAKA Labs
All publications →A Computational Model for Improving Spare Network Intermittent Connectivity Problems in Vehicular Ad Hoc Networks (Vanets)Journal article
Training-Free Open-Vocabulary 3D Point-Cloud Segmentation on the Generalized Few-Shot BenchmarkJournal article · 2026
Training-Free Generalized Few-Shot Segmentation through Open-Vocabulary Semantic ArbitrationJournal article · 2026
A comparative study of explainability methods for time-series forecasting of blood glucose levelsJournal article · 2026