Towards domain adaptation with open-set target data: Review of theory and computer vision applications R1# C1
Open-set domain adaptation is a develo** and practical solution to training deep networks
using unlabeled data which have been collected among unknown data and are under …
using unlabeled data which have been collected among unknown data and are under …
Multi-source EEG emotion recognition via dynamic contrastive domain adaptation
Y **ao, Y Zhang, X Peng, S Han, X Zheng… - … Signal Processing and …, 2025 - Elsevier
Electroencephalography (EEG) provides reliable indications of human cognition and mental
states. Accurate emotion recognition from EEG remains challenging due to signal variations …
states. Accurate emotion recognition from EEG remains challenging due to signal variations …
Cross-domain video action recognition via adaptive gradual learning
Abstract Video-based Unsupervised Domain Adaptation (UDA) methods concentrate on
addressing domain shift and improving the robustness of video models. It can be naturally …
addressing domain shift and improving the robustness of video models. It can be naturally …
Augmenting and Aligning Snippets for Few-Shot Video Domain Adaptation
For video models to be transferred and applied seamlessly across video tasks in varied
environments, Video Unsupervised Domain Adaptation (VUDA) has been introduced to …
environments, Video Unsupervised Domain Adaptation (VUDA) has been introduced to …
Leveraging Endo-and Exo-Temporal Regularization for Black-box Video Domain Adaptation
To enable video models to be applied seamlessly across video tasks in different
environments, various Video Unsupervised Domain Adaptation (VUDA) methods have been …
environments, various Video Unsupervised Domain Adaptation (VUDA) methods have been …
Key Design Choices in Source-Free Unsupervised Domain Adaptation: An In-depth Empirical Analysis
This study provides a comprehensive benchmark framework for Source-Free Unsupervised
Domain Adaptation (SF-UDA) in image classification, aiming to achieve a rigorous empirical …
Domain Adaptation (SF-UDA) in image classification, aiming to achieve a rigorous empirical …
Source-free video domain adaptation by learning from noisy labels
Despite the progress seen in classification methods, current approaches for handling videos
with distribution shifts in source and target domains remain source-dependent as they …
with distribution shifts in source and target domains remain source-dependent as they …
LEARN: A Unified Framework for Multi-Task Domain Adapt Few-Shot Learning
B Ravichandran, A Lynch, S Brockman… - arxiv preprint arxiv …, 2024 - arxiv.org
Both few-shot learning and domain adaptation sub-fields in Computer Vision have seen
significant recent progress in terms of the availability of state-of-the-art algorithms and …
significant recent progress in terms of the availability of state-of-the-art algorithms and …
Deep Unsupervised Domain Adaptation for Time Series Classification: a Benchmark
HI Fawaz, G Del Grosso, T Kerdoncuff… - arxiv preprint arxiv …, 2023 - arxiv.org
Unsupervised Domain Adaptation (UDA) aims to harness labeled source data to train
models for unlabeled target data. Despite extensive research in domains like computer …
models for unlabeled target data. Despite extensive research in domains like computer …
Video Domain Incremental Learning for Human Action Recognition in Home Environments
It is significantly challenging to recognize daily human actions in homes due to the diversity
and dynamic changes in unconstrained home environments. It spurs the need to continually …
and dynamic changes in unconstrained home environments. It spurs the need to continually …