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 …
Md. Mahbubur Rahman
PhD in Computer Science, in progress
2025-01-01
University of Wyoming
MSc in Computer Science and Engineering
2016-01-01
2020-12-31
Mawlana Bhashani Science and Technology University
BSc in Computer Science and Engineering
2012-01-01
2016-12-31
Mawlana Bhashani Science and Technology University
I develop computer vision methods that use RGB-D observations to study plant structure and growth. My current work brings together trait estimation, temporal evidence for recovering occluded leaves, and 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 …
TAHAF uses trait-adaptive hierarchical attention fusion to combine RGB and depth information for lettuce phenotyping in hydroponic systems.
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 …
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