Md. Mahbubur Rahman

Temporal amodal leaf completion

This project investigates recovery of occluded plant leaves using RGB-D observations and an identity-matched history across days. The methodology separates mask reconstruction from …

TAHAF: RGB-D plant phenotyping

TAHAF uses trait-adaptive hierarchical attention fusion to combine RGB and depth information for lettuce phenotyping in hydroponic systems.

CLFM: climate-informed representation learning

CLFM explores label-efficient plant trait prediction by bringing greenhouse images and climate measurements into a shared learning framework. Current development investigates …

Attention-Based Task-Adaptive Fusion for Real-Time RGB-D Lettuce Morphological Analysis

ASABE Annual International Meeting 2026, Indianapolis, Indiana.

TAHAF: Trait Adaptive Hierarchical Attention Fusion of RGB-D data for automated lettuce phenotyping in hydroponic systems

AirNet: Predictive machine learning model for air quality forecasting

Hybrid feature fusion and CNN for melanoma skin cancer detection

BreastMultiNet: Multi-scale feature fusion for breast cancer detection