Portfolio

Projects

Research, systems, and tools built at the intersection of artificial intelligence, computer vision, and applied problem-solving.

active

Forest species identification from macroscopic wood images

Benchmarking YOLO models (v8, 11, and 26) for automated identification of 73 forest species from macroscopic wood images. Achieved 99.87% accuracy with YOLO26m across heterogeneous datasets.

Computer VisionDeep LearningYOLO26t-SNEOOD
t-SNE Classifier

More projects coming soon

Ongoing research will be published here as it is completed.