Project
Plant Segmentation using U-Net
Implemented U-Net from scratch for semantic segmentation of plant images.
sackline naien ridviBRAC University
sackline naien ridvi
Computer Science graduate with a strong interest in software development, Data Science & Machine Learning
BRAC University
Project
Implemented U-Net from scratch for semantic segmentation of plant images.
Project
Predicted AQI across all Bangladesh districts using an ensemble of 8 models; achieved 76% accuracy.
Project
Full-stack travel platform with itinerary planning, booking, expense tracking, and payment API integration.
Project
Classified disease stages using ML models; best result 87.44% accuracy (Decision Tree).