5 papers
DistMedVL: Distributional Vision-Language Alignment for Uncertainty-Aware Medical Image Segmentation
Jiaxuan Li, Qing Xu, Xiangjian He +4
Cross-modal alignment of visual and textual representations is fundamental to multimodal medical image understanding, yet remains hindered by uncertainty in both modalities under r…
MCD-Net: A Lightweight Deep Learning Baseline for Optical-Only Moraine Segmentation
Zhehuan Cao, Fiseha Berhanu Tesema, Ping Fu +2
Glacial segmentation is essential for reconstructing past glacier dynamics and evaluating climate-driven landscape change. However, weak optical contrast and the limited availabili…
LGPS: A Lightweight GAN-Based Approach for Polyp Segmentation in Colonoscopy Images
Fiseha B. Tesema, Alejandro Guerra Manzanares, Tianxiang Cui +3
Colorectal cancer (CRC) is a major global cause of cancer-related deaths, with early polyp detection and removal during colonoscopy being crucial for prevention. While deep learnin…
De-LightSAM: Modality-Decoupled Lightweight SAM for Generalizable Medical Segmentation
Qing Xu, Jiaxuan Li, Xiangjian He +8
The universality of deep neural networks across different modalities and their generalization capabilities to unseen domains play an essential role in medical image segmentation. T…
Hybrid Channel Based Pedestrian Detection
Fiseha B. Tesema, Hong Wu, Mingjian Chen +3
Pedestrian detection has achieved great improvements with the help of Convolutional Neural Networks (CNNs). CNN can learn high-level features from input images, but the insufficien…