33 citations · 43 across the 6 of their papers we have counts for
6 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…
End-To-End Audiovisual Feature Fusion for Active Speaker Detection
Fiseha B. Tesema, Zheyuan Lin, Shiqiang Zhu +3
Active speaker detection plays a vital role in human-machine interaction. Recently, a few end-to-end audiovisual frameworks emerged. However, these models' inference time was not e…
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…