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   Articles with "unsupervised domain" as a keyword



Unsupervised Domain Adaptation for Simultaneous Segmentation and Classification of the Retinal Arteries and Veins

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recommendations! Published in 2024 at "International Journal of Imaging Systems and Technology"

DOI: 10.1002/ima.23151

Abstract: Automatic segmentation of the fundus retinal vessels and accurate classification of the arterial and venous vessels play an important role in clinical diagnosis. This article proposes a fundus retinal vascular segmentation and arteriovenous classification network… read more here.

Keywords: classification; unsupervised domain; segmentation; classification retinal ... See more keywords

Histogram matching‐enhanced adversarial learning for unsupervised domain adaptation in medical image segmentation

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recommendations! Published in 2025 at "Medical Physics"

DOI: 10.1002/mp.17757

Abstract: Unsupervised domain adaptation (UDA) seeks to mitigate the performance degradation of deep neural networks when applied to new, unlabeled domains by leveraging knowledge from source domains. In medical image segmentation, prevailing UDA techniques often utilize… read more here.

Keywords: adversarial learning; adaptation; unsupervised domain; segmentation ... See more keywords

Unsupervised domain adaptation with target reconstruction and label confusion in the common subspace

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recommendations! Published in 2018 at "Neural Computing and Applications"

DOI: 10.1007/s00521-018-3846-x

Abstract: Deep neural networks can learn powerful and discriminative representations from a large number of labeled samples. However, it is typically costly to collect and annotate large-scale datasets, which limits the applications of deep learning in… read more here.

Keywords: reconstruction; domain; target; domain adaptation ... See more keywords

Bi-directional class-wise adversaries for unsupervised domain adaptation

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recommendations! Published in 2021 at "Applied Intelligence"

DOI: 10.1007/s10489-021-02609-7

Abstract: Unsupervised domain adaptation relies on well-labeled auxiliary source domain information to get better performance on the unlabeled target domain. It has shown tremendous importance for various classification and segmentation problems. Classical methods rely on diminishing… read more here.

Keywords: class; class wise; domain adaptation; domain ... See more keywords

Terrain traversability prediction through self-supervised learning and unsupervised domain adaptation on synthetic data

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recommendations! Published in 2024 at "Autonomous Robots"

DOI: 10.1007/s10514-024-10158-4

Abstract: Terrain traversability estimation is a fundamental task for supporting robot navigation on uneven surfaces. Recent learning-based approaches for predicting traversability from RGB images have shown promising results, but require manual annotation of a large number… read more here.

Keywords: domain adaptation; unsupervised domain; navigation; traversability ... See more keywords

CLDA: an adversarial unsupervised domain adaptation method with classifier-level adaptation

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recommendations! Published in 2020 at "Multimedia Tools and Applications"

DOI: 10.1007/s11042-020-08877-8

Abstract: Domain adaptation is an active and important research field in transfer learning. Unsupervised domain adaptation, which is better in line with real-world scenarios than supervised and semi-supervised domain adaptation, has attracted much attention and research.… read more here.

Keywords: adversarial unsupervised; domain; level; domain adaptation ... See more keywords
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Adversarial unsupervised domain adaptation for 3D semantic segmentation with multi-modal learning

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recommendations! Published in 2021 at "Isprs Journal of Photogrammetry and Remote Sensing"

DOI: 10.1016/j.isprsjprs.2021.04.012

Abstract: Abstract Semantic segmentation in 3D point-clouds plays an essential role in various applications, such as autonomous driving, robot control, and mapping. In general, a segmentation model trained on one source domain suffers a severe decline… read more here.

Keywords: domain adaptation; unsupervised domain; semantic segmentation; segmentation ... See more keywords

Target-aware cross-modality unsupervised domain adaptation for vestibular schwannoma and cochlea segmentation

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recommendations! Published in 2024 at "Scientific Reports"

DOI: 10.1038/s41598-024-77633-x

Abstract: There is growing interest in research on segmentation for the vestibular schwannoma (VS) and cochlea using high-resolution T2 (hrT2) imaging over contrast-enhanced T1 (ceT1) imaging due to the contrast agent side effects. However, the hrT2… read more here.

Keywords: unsupervised domain; segmentation; target aware; domain adaptation ... See more keywords

Diffusion‐UDA: Diffusion‐based unsupervised domain adaptation for submersible fault diagnosis

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recommendations! Published in 2024 at "Electronics Letters"

DOI: 10.1049/ell2.13122

Abstract: Deep learning has demonstrated notable success in mechanical signal processing with a large amount labelled data. However, the systems of the Jiaolong deep‐sea submersible prone to malfunction are typically diverse, due to the high complexity… read more here.

Keywords: unsupervised domain; diffusion based; domain adaptation; diffusion ... See more keywords
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Symmetric co-training based unsupervised domain adaptation approach for intelligent fault diagnosis of rolling bearing

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recommendations! Published in 2020 at "Measurement Science and Technology"

DOI: 10.1088/1361-6501/ab9841

Abstract: Conventional intelligent diagnostic model is built on the foundation that the training data and testing data are recorded under the same operating condition, which neglects the fact that the operating condition of the rotating machinery… read more here.

Keywords: symmetric training; operating condition; training; domain adaptation ... See more keywords

Bearing fault diagnosis under variable speed conditions based on time series mixup and unsupervised domain adaptation

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recommendations! Published in 2025 at "Measurement Science and Technology"

DOI: 10.1088/1361-6501/adc4fd

Abstract: The operation of rolling bearings under practical conditions often involves variable speed, which results in non-stationary vibrations. Extracting time-varying fault frequencies effectively from these non-stationary vibration signals due to speed fluctuations poses a significant challenge… read more here.

Keywords: unsupervised domain; speed; fault diagnosis; variable speed ... See more keywords