Results 161 to 170 of about 3,036,262 (193)
Unsupervised Domain Adaptation with Raman Spectroscopy for Rapid Autoimmune Disease Diagnosis. [PDF]
Zhang Z, Liu Y, Chen C, Lv X, Chen C.
europepmc +1 more source
RESAMPL-UDA: Leveraging foundation models for unsupervised domain adaptation in biomedical images
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
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SF-UDA3D: Source-Free Unsupervised Domain Adaptation for LiDAR-Based 3D Object Detection [PDF]
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
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IEEE Transactions on Aerospace and Electronic Systems, 2022
Hao Chen, Jingzhi Guo, Zhiguo Gong
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Hao Chen, Jingzhi Guo, Zhiguo Gong
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Cascade-UDA: A Cascade paradigm for unsupervised domain adaptation
NeurocomputingXiaofeng Zhu, Rongyao Hu
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Mamba-UDA: Mamba Unsupervised Domain Adaptation for SAR Ship Detection
IEEE Geoscience and Remote Sensing LettersShiqi Chen
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MS-UDA: Multi-Spectral Unsupervised Domain Adaptation for Thermal Image Semantic Segmentation
IEEE Robotics and Automation Letters, 2021In 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 MedicineGliomas 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
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