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   Articles with "source free" as a keyword



Lightweight Source-Free Domain Adaptation Based on Adaptive Euclidean Alignment for Brain-Computer Interfaces

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recommendations! Published in 2024 at "IEEE Journal of Biomedical and Health Informatics"

DOI: 10.1109/jbhi.2024.3463737

Abstract: For privacy protection of subjects in electroencephalogram (EEG)-based brain-computer interfaces (BCIs), using source-free domain adaptation (SFDA) for cross-subject recognition has proven to be highly effective. However, updating and storing a model trained on source subjects… read more here.

Keywords: euclidean alignment; source free; brain computer; source ... See more keywords

Federated Spatial Prior-Based Source-Free Domain Adaptation for White Matter Hyperintensities Segmentation.

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recommendations! Published in 2025 at "IEEE journal of biomedical and health informatics"

DOI: 10.1109/jbhi.2025.3612029

Abstract: White matter hyperintensities (WMH) are important imaging biomarkers for cerebral small vessel disease, and their automatic segmentation across data with different distributions is crucial for assessing brain health and supporting diagnosis. However, cross-domain WMH segmentation… read more here.

Keywords: white matter; source free; segmentation; matter hyperintensities ... See more keywords

Tunable Multiwavelength Optical Comb Enabled WDM-OFDM-PON With Source-Free ONUs

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recommendations! Published in 2018 at "IEEE Photonics Journal"

DOI: 10.1109/jphot.2018.2827306

Abstract: In this paper, we propose and experimentally demonstrate a multiuser wavelength-division-multiplexing passive optical network (WDM-PON) system combining with orthogonal frequency division multiple (OFDM) technique. A tunable multiwavelength optical comb (MOC) is designed to supply flat… read more here.

Keywords: pon; source free; optical comb; ofdm pon ... See more keywords

Adversarial Source Generation for Source-Free Domain Adaptation

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recommendations! Published in 2024 at "IEEE Transactions on Circuits and Systems for Video Technology"

DOI: 10.1109/tcsvt.2023.3337796

Abstract: Unsupervised domain adaptation aims to transfer the knowledge learned from a labeled source domain to an unlabeled target domain with different data distributions. However, in practice, source samples are not always available due to privacy… read more here.

Keywords: adaptation; source free; generation; source ... See more keywords

Exploring Relational Knowledge for Source-Free Domain Adaptation

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recommendations! Published in 2025 at "IEEE Transactions on Circuits and Systems for Video Technology"

DOI: 10.1109/tcsvt.2024.3484761

Abstract: Standard domain adaptation methods require access to both source and target data. However, sharing source data is often impractical in real-world scenarios due to data privacy and memory limitation issues. In this work, we focus… read more here.

Keywords: adaptation; source free; free domain; domain adaptation ... See more keywords

Source-Free Domain Adaptive Detection of Concealed Objects in Passive Millimeter-Wave Images

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recommendations! Published in 2023 at "IEEE Transactions on Instrumentation and Measurement"

DOI: 10.1109/tim.2023.3237816

Abstract: Passive millimeter-wave (PMMW) imager can detect concealed objects under clothing in a touch-free manner. Existing detectors exhibit promising performance on specific PMMW datasets. However, these detectors will suffer severe degradation due to the inevitable domain… read more here.

Keywords: domain; source; millimeter wave; concealed objects ... See more keywords

Imbalanced Source-Free Adaptation Diagnosis for Rotating Machinery

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recommendations! Published in 2024 at "IEEE Transactions on Instrumentation and Measurement"

DOI: 10.1109/tim.2024.3400354

Abstract: There have been some studies on fault diagnosis in source-free domain adaptation (SFDA) environments, but, currently, all studies assume that the fault types are uniform. When fault diagnosis under imbalanced fault categories is studied, negative… read more here.

Keywords: diagnosis; adaptation; source free; fault diagnosis ... See more keywords

Visually Source-Free Domain Adaptation via Adversarial Style Matching

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recommendations! Published in 2024 at "IEEE Transactions on Image Processing"

DOI: 10.1109/tip.2024.3353539

Abstract: The majority of existing works explore Unsupervised Domain Adaptation (UDA) with an ideal assumption that samples in both domains are available and complete. In real-world applications, however, this assumption does not always hold. For instance,… read more here.

Keywords: style; source free; source; domain adaptation ... See more keywords

Consistent Assistant Domains Transformer for Source-Free Domain Adaptation

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recommendations! Published in 2025 at "IEEE Transactions on Image Processing"

DOI: 10.1109/tip.2025.3611799

Abstract: Source-free domain adaptation (SFDA) aims to address the challenge of adapting to a target domain without accessing the source domain directly. However, due to the inaccessibility of source domain data, deterministic invariable features cannot be… read more here.

Keywords: domain; source free; free domain; source ... See more keywords

Self-Mining the Confident Prototypes for Source-Free Unsupervised Domain Adaptation in Image Segmentation

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recommendations! Published in 2024 at "IEEE Transactions on Multimedia"

DOI: 10.1109/tmm.2024.3370678

Abstract: This paper studies a practical Source-free unsupervised domain adaptation (SFUDA) problem, which transfers knowledge of source-trained models to the target domain, without accessing the source data. It has received increasing attention in recent years, while… read more here.

Keywords: adaptation; unsupervised domain; source free; source ... See more keywords

Domain-Division Based Progressive Learning for Source-Free Domain Adaptation

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recommendations! Published in 2025 at "IEEE Transactions on Multimedia"

DOI: 10.1109/tmm.2025.3590903

Abstract: With growing privacy and portability concerns, source-free domain adaptation requires only a source pre-trained model and an unlabeled target domain, allowing for effective adaptation to the target data. Most existing self-training methods focus on selecting… read more here.

Keywords: adaptation; source free; free domain; division ... See more keywords