Detectron2-enhanced mask R-CNN for precise instance segmentation of rice blast disease in Tanzania: Supporting timely intervention and data-driven severity assessment

Relationship between rice blast severity and the rice growth stage for accurate selection of rice breeding material for improved rice production in Africa

Mask region-based convolutional neural network (R-CNN) models for extracting building footprints from remote sensing data

These trained deep learning are trained to extract building footprints from high-resolu

Cropping System to Limit Blast Disease in Upland Rice

International audience Cropping system is an essential aspect to take into account to

brakuta/Datepalm-Instance-Segmentation

Code for date-palm crown instance segmentation with CNN, transformer and state-space (Mamba) backbon

Building Instance Segmentation for Dense Urban Settlements

About 25\% of the world’s population live in informal urban settlements containing densely packed bu

MAIN: Multi-Attention Instance Network for Video Segmentation

Instance-level video segmentation requires a solid integration of spatial and temporal information.