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Found 4 papers, 1 papers with code
A Chebyshev Confidence Guided Source-Free Domain Adaptation Framework for Medical Image Segmentation
Source-free domain adaptation (SFDA) aims to adapt models trained on a labeled source domain to an unlabeled target domain without the access to source data.
DECOR-NET: A COVID-19 Lung Infection Segmentation Network Improved by Emphasizing Low-level Features and Decorrelating Features
Since 2019, coronavirus Disease 2019 (COVID-19) has been widely spread and posed a serious threat to public health.
Evaluation of Multimodal Semantic Segmentation using RGB-D Data
Our goal is to develop stable, accurate, and robust semantic scene understanding methods for wide-area scene perception and understanding, especially in challenging outdoor environments.
CalibDNN: Multimodal Sensor Calibration for Perception Using Deep Neural Networks
Current perception systems often carry multimodal imagers and sensors such as 2D cameras and 3D LiDAR sensors.
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