Results 161 to 170 of about 3,036,262 (193)

RESAMPL-UDA: Leveraging foundation models for unsupervised domain adaptation in biomedical images

open access: yesPattern Recognition Letters
International audienceLarge annotated datasets and new models have led to significant improvements in supervised semantic segmentation. On the other side, Unsupervised Domain Adaptation (UDA) for Semantic Segmentation is still an arduous open research ...
Nicolas Passat, Benoit Naegel
exaly   +5 more sources

SF-UDA3D: Source-Free Unsupervised Domain Adaptation for LiDAR-Based 3D Object Detection [PDF]

open access: yes2020 International Conference on 3D Vision (3DV), 2020
International audience3D object detectors based only on LiDAR point clouds hold the state-of-the-art on modern street-view benchmarks. However, LiDAR-based detectors poorly generalize across domains due to domain shift.
Stéphane Lathuilière   +2 more
exaly   +9 more sources

NI-UDA: Graph Contrastive Domain Adaptation for Nonshared-and-Imbalanced Unsupervised Domain Adaptation

IEEE Transactions on Aerospace and Electronic Systems, 2022
Hao Chen, Jingzhi Guo, Zhiguo Gong
exaly   +3 more sources

MS-UDA: Multi-Spectral Unsupervised Domain Adaptation for Thermal Image Semantic Segmentation

IEEE Robotics and Automation Letters, 2021
In this letter, we propose a multi-spectral unsupervised domain adaptation for thermal image semantic segmentation. The proposed framework aims to address the data scarcity problem and boost segmentation performance in the thermal domain with the help of existing large-scale RGB datasets and segmentation knowledge from an RGB image segmentation network.
Yeong-Hyeon Kim   +3 more
openaire   +2 more sources

UDA-GS: A cross-center multimodal unsupervised domain adaptation framework for Glioma segmentation

Computers in Biology and Medicine
Gliomas are the most common and malignant form of primary brain tumors. Accurate segmentation and measurement from MRI are crucial for diagnosis and treatment. Due to the infiltrative growth pattern of gliomas, their labeling is very difficult. In turn, the already available annotated datasets, such as well-known BraTS, are difficult to generalize to ...
Yuhao Sun, Jinhua Yu, Zheng Zhao
exaly   +3 more sources

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