Results 101 to 110 of about 3,036,262 (193)
CoRRUnsupervised domain adaptation for medical image segmentation remains a significant challenge due to substantial domain shifts across imaging modalities, such as CT and MRI. While recent vision-language representation learning methods have shown promise, their potential in UDA segmentation tasks remains underexplored.
Lalit Maurya +2 more
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Enhancing Plant Disease Classification through Unsupervised Domain Adaptation (UDA)
Classification models of plant diseases have been proven to show significant accuracy when trained and tested within a well-controlled laboratory environment but show poor performance when tested on real farming environments, where there is a domain ...
Nadigottu, Raj
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Unsupervised Domain Adaptation Using Compact Internal Representations [PDF]
A major technique for tackling unsupervised domain adaptation involves mapping data points from both the source and target domains into a shared embedding space.
Rostami, Mohammad
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Remote SensingRemote sensing scene classification is one of the crucial techniques for high-resolution remote sensing image interpretation and has received widespread attention in recent years.
Jiahao Wei, Erzhu Li, Ce Zhang
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On Fine-Tuned Deep Features for Unsupervised Domain Adaptation
, 2022 Prior feature transformation based approaches to Unsupervised Domain Adaptation (UDA) employ the deep features extracted by pre-trained deep models without fine-tuning them on the specific source or target domain data for a particular domain adaptation ...
Breckon, Toby P., Wang, Qian
core
CoRRThe scarcity and complexity of voxel-level annotations in 3D medical imaging present significant challenges, particularly due to the domain gap between labeled datasets from well-resourced centers and unlabeled datasets from less-resourced centers. This disparity affects the fairness of artificial intelligence algorithms in healthcare.
Haifan Gong +5 more
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Scale-Consistent and Temporally Ensembled Unsupervised Domain Adaptation for Object Detection
SensorsUnsupervised Domain Adaptation for Object Detection (UDA-OD) aims to adapt a model trained on a labeled source domain to an unlabeled target domain, addressing challenges posed by domain shifts. However, existing methods often face significant challenges,
Lunfeng Guo +4 more
doaj +1 more source
Informative feature disentanglement for unsupervised domain adaptation
, 2022 Unsupervised Domain Adaptation (UDA) aims at learning a classifier for an unlabeled target domain by transferring knowledge from a labeled source domain with a related but different distribution. The strategy of aligning the two domains in latent feature
Pietikäinen, M. (Matti) +7 more
core
IEEE Journal of Selected Topics in Applied Earth Observations and Remote SensingIn this study, we propose a robust debris estimation model applied to satellite imagery that is suitable for practical applications. In our previous study, we proposed a coastal marine debris estimation model using semantic segmentation applied to very ...
Kenichi Sasaki +2 more
doaj +1 more source
Domain-Constraint Transfer Coding for Imbalanced Unsupervised Domain Adaptation
, 2016 Unsupervised domain adaptation (UDA) deals with the task that labeled training and unlabeled test data collected from source and target domains, respectively.
Wang, Yu-Chiang Frank +4 more
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