Return of Frustratingly Easy Domain Adaptation

ImageNet classification with deep convolutional neural networks

Krizhevsky, A., Sutskever, I., & Hinton, G. E. (2017) · Communications of the ACM · doi:10.1145/3065386 · Cited by 112,155

ImageNet: A large-scale hierarchical image database

Deng, J., Dong, W., Socher, R., Li, L.-J., Li, K., & Fei-Fei, L. (2009) · 2009 IEEE Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2009.5206848 · Cited by 65,333

Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift

Ioffe, S., & Szegedy, C. (2015) · arXiv · doi:10.48550/arxiv.1502.03167 · Cited by 27,818

A Singular Value Thresholding Algorithm for Matrix Completion

Cai, J., Candès, E. J., & Shen, Z. (2010) · SIAM Journal on Optimization · doi:10.1137/080738970 · Cited by 5,878

Unsupervised Domain Adaptation by BackpropagationPreprint

Ganin, Y., & Lempitsky, V. (2014) · arXiv (Cornell University) · doi:10.48550/arxiv.1409.7495 · Cited by 5,441

Domain Adaptation via Transfer Component Analysis

Pan, S. J., Tsang, I. W.-H., Kwok, J. T.-Y., & Yang, Q. (2010) · IEEE Transactions on Neural Networks · doi:10.1109/tnn.2010.2091281 · Cited by 4,809

Learning Transferable Features with Deep Adaptation Networks

Long, M., Cao, Y., Wang, J., & Jordan, M. I. (2015) · arXiv · doi:10.48550/arxiv.1502.02791 · Cited by 4,505

DeCAF: A Deep Convolutional Activation Feature for Generic Visual Recognition

Donahue, J., Jia, Y., Vinyals, O., Hoffman, J., Zhang, N., Tzeng, E., & Darrell, T. (2013) · arXiv · doi:10.48550/arxiv.1310.1531 · Cited by 4,019

SUN database: Large-scale scene recognition from abbey to zoo

Xiao, J., Hays, J., Ehinger, K. A., Oliva, A., & Torralba, A. (2010) · 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2010.5539970 · Cited by 3,283

Adapting visual category models to new domains

Saenko, K., Kulis, B., Fritz, M., & Darrell, T. (2010) · Lecture Notes in Computer Science · doi:10.1007/978-3-642-15561-1_16 · Cited by 2,847

Ship Classification in SAR Images With Geometric Transfer Metric Learning

Xu, Y., & Lang, H. (2020) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2020.3026387 · Cited by 40

Toward Long-Term Effective and Robust Device-Free Indoor Localization via Channel State Information

Li, Z. Z., & Rao, X. (2021) · IEEE Internet of Things Journal · doi:10.1109/jiot.2021.3098019 · Cited by 41

Median Stable Clustering and Global Distance Classification for Cross-Domain Person Re-Identification

Pang, Z., Guo, J., Zhi-qiang, M., Sun, W., & Xiao, Y. (2021) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2021.3103753 · Cited by 41

BuresNet: Conditional Bures Metric for Transferable Representation Learning

Ren, C.-X., Luo, Y.-W., & Dai, D. (2022) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2022.3190645 · Cited by 42

ToAlign: Task-oriented Alignment for Unsupervised Domain AdaptationPreprint

Wei, G., Lan, C., Zeng, W., Zhang, Z., & Chen, Z. (2021) · arXiv (Cornell University) · doi:10.48550/arxiv.2106.10812 · Cited by 40

EBCDet: Energy-Based Curriculum for Robust Domain Adaptive Object Detection

Banitalebi-Dehkordi, A., Amirkhani, A., & Mohammadinasab, A. (2023) · IEEE Access · doi:10.1109/access.2023.3298369 · Cited by 44

Source-Free Domain Adaptation for Privacy-Preserving Seizure Prediction

Zhao, Y., Feng, S., Li, C., Song, R., Deng, L., & Chen, X. (2023) · IEEE Transactions on Industrial Informatics · doi:10.1109/tii.2023.3297323 · Cited by 39

A cross-session motor imagery classification method based on Riemannian geometry and deep domain adaptation

Liu, W., Guo, C., & Gao, C. (2023) · Expert Systems with Applications · doi:10.1016/j.eswa.2023.121612 · Cited by 40

Domain-adaptive neural networks improve supervised machine learning based on simulated population genetic data

Mo, Z., & Siepel, A. C. (2023) · PLoS Genetics · doi:10.1371/journal.pgen.1011032 · Cited by 43

Fault Diagnosis of Delta 3D Printers Using Transfer Support Vector Machine With Attitude Signals

Guo, J., Wu, J., Sun, Z., Long, J., & Zhang, S. (2019) · IEEE Access · doi:10.1109/access.2019.2905264 · Cited by 39

Iterative Refinement for Multi-source Visual Domain Adaptation

Wu, H., Yan, Y., Lin, G., Yang, M., Ng, M. K., & Wu, Q. (2020) · IEEE Transactions on Knowledge and Data Engineering · doi:10.1109/tkde.2020.3014697 · Cited by 39

Multiscale Transfer Voting Mechanism: A New Strategy for Domain Adaption

Qin, Y., Wang, X., Qian, Q., Pu, H., & Luo, J. (2020) · IEEE Transactions on Industrial Informatics · doi:10.1109/tii.2020.3045392 · Cited by 39

Information-theoretic regularization for Multi-source Domain Adaptation

Park, G. Y., & Lee, S. W. (2021) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv48922.2021.00908 · Cited by 42

Prototype-Based Multisource Domain Adaptation

Zhou, L., Ye, M., Zhang, D., Zhu, C., & Ji, L. (2021) · IEEE Transactions on Neural Networks and Learning Systems · doi:10.1109/tnnls.2021.3070085 · Cited by 39

Cross-Domain Sentiment Classification with Contrastive Learning and Mutual Information Maximization

Li, T., Chen, X., Zhang, S., Dong, Z. X., & Keutzer, K. (2021) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp39728.2021.9414930 · Cited by 40

Learning Factorized Representations for Open-set Domain AdaptationPreprint

Baktashmotlagh, M., Faraki, M., Drummond, T. W., & Salzmann, M. (2018) · arXiv (Cornell University) · doi:10.48550/arxiv.1805.12277 · Cited by 41

Partial Domain Adaptation Without Domain Alignment

Li, W., & Chen, S. (2022) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2022.3228937 · Cited by 39

Addressing cross-population domain shift in chest X-ray classification through supervised adversarial domain adaptation

Musa, A., Prasad, R., & Hernandez, M. (2025) · Scientific Reports · doi:10.1038/s41598-025-95390-3 · Cited by 48

Cross-Dataset Adaptation for Visual Question Answering

Sha, F., Hu, H., & Chao, W. (2018) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2018.00599 · Cited by 41

Unsupervised Domain Adaptation for Micro-Doppler Human Motion Classification via Feature Fusion

Lang, Y., Wang, Q., Yang, Y., Hou, C., Huang, D., & Xiang, W. (2018) · IEEE Geoscience and Remote Sensing Letters · doi:10.1109/lgrs.2018.2873776 · Cited by 38

Dual-Representation-Based Autoencoder for Domain Adaptation

Yang, S., Yu, K., Cao, F., Wang, H., & Wu, X. (2021) · IEEE Transactions on Cybernetics · doi:10.1109/tcyb.2020.3040763 · Cited by 38

Unraveling the heterogeneity in Alzheimer's disease progression across multiple cohorts and the implications for data‐driven disease modeling

Birkenbihl, C., Salimi, Y., Fröhlich, H., Initiative, F. T. J. A. D. N., & Initiative, T. A. D. N. (2021) · Alzheimer s & Dementia · doi:10.1002/alz.12387 · Cited by 39

Cross-domain person re-identification by hybrid supervised and unsupervised learning

Pang, Z., Guo, J., Sun, W., Xiao, Y., & Yu, M. Y. (2021) · Applied Intelligence · doi:10.1007/s10489-021-02551-8 · Cited by 39

Learning transfer feature representations for gas path fault diagnosis across gas turbine fleet

Li, B., Zhao, Y.-P., & Chen, Y.-B. (2022) · Engineering Applications of Artificial Intelligence · doi:10.1016/j.engappai.2022.104733 · Cited by 38

Syn2Real: A New Benchmark forSynthetic-to-Real Visual Domain AdaptationPreprint

Peng, X., Usman, B., Saito, K., Kaushik, N., Hoffman, J., & Saenko, K. (2018) · arXiv (Cornell University) · doi:10.48550/arxiv.1806.09755 · Cited by 56

Rethinking Distributional Matching Based Domain AdaptationPreprint

Li, B., Wang, Y., Che, T., Zhang, S., Zhao, S., Xu, P., Zhou, W., Bengio, Y., & Keutzer, K. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2006.13352 · Cited by 60

Adversarial Domain Adaptation Network With Calibrated Prototype and Dynamic Instance Convolution for Hyperspectral Image Classification

Huang, Y., Peng, J., Zhang, G., Sun, W., Chen, N., & Du, Q. (2024) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2024.3387990 · Cited by 37

Unsupervised Domain Adaptation by Matching Distributions Based on the Maximum Mean Discrepancy via Unilateral Transformations

Kumagai, A., & Iwata, T. (2019) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v33i01.33014106 · Cited by 37

Unsupervised domain adaptation with progressive adaptation of subspaces

Li, W., & Chen, S. (2022) · Pattern Recognition · doi:10.1016/j.patcog.2022.108918 · Cited by 37

From Big to Small: Adaptive Learning to Partial-Set Domains

Cao, Z., You, K., Zhang, Z., Wang, J., & Long, M. (2022) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2022.3159831 · Cited by 38

Generation, augmentation, and alignment: a pseudo-source domain based method for source-free domain adaptation

Du, Y., Yang, H., Chen, M., Luo, H., Jiang, J., Xin, Y., & Wang, C. (2023) · Machine Learning · doi:10.1007/s10994-023-06432-8 · Cited by 47

Feature Alignment and Restoration for Domain Generalization and AdaptationPreprint

Jin, X., Lan, C., Zeng, W., & Chen, Z. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2006.12009 · Cited by 61

Stream Temperature Prediction in a Shifting Environment: Explaining the Influence of Deep Learning Architecture

Topp, S., Barclay, J. R., Diaz, J., Sun, A. Y., Jia, X., Lu, D., Sadler, J. M., & Appling, A. (2023) · Water Resources Research · doi:10.1029/2022wr033880 · Cited by 36

Integrated decision-making with adaptive feature weighting adversarial network for multi-target domain compound fault diagnosis of machinery

Zhang, X., Wang, J., Zhang, Z., Han, B., Bao, H., & Jiang, X. (2024) · Advanced Engineering Informatics · doi:10.1016/j.aei.2024.102730 · Cited by 36

Unsupervised Adversarial Domain Adaptation Network for Semantic Segmentation

Liu, W., & Su, F. (2019) · IEEE Geoscience and Remote Sensing Letters · doi:10.1109/lgrs.2019.2956490 · Cited by 36

Unsupervised Domain Adaptation via Discriminative Manifold Embedding and Alignment

Luo, Y.-W., Ren, C.-X., Ge, P., Huang, K.-K., & Yu, Y. (2020) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v34i04.5943 · Cited by 36

Cross-Machine Fault Diagnosis with Semi-Supervised Discriminative Adversarial Domain Adaptation

Wang, X., Liu, F., & Zhao, D. (2020) · Sensors · doi:10.3390/s20133753 · Cited by 39

Learning joint segmentation of tissues and brain lesions from task-specific hetero-modal domain-shifted datasets

Dorent, R., Booth, T. C., Li, W., Sudre, C. H., Kafiabadi, S., Cardoso, M. J., Sebastien Ourselin, A., & Vercauteren, T. K. (2020) · Medical Image Analysis · doi:10.1016/j.media.2020.101862 · Cited by 36

Toward Personalized Affect-Aware Socially Assistive Robot Tutors for Long-Term Interventions with Children with Autism

Shi, Z., Groechel, T. R., Jain, S., Chima, K., Rudovic, O. O., & Matarić, M. J. (2022) · ACM Transactions on Human-Robot Interaction · doi:10.1145/3526111 · Cited by 43

Tune it the Right Way: Unsupervised Validation of Domain Adaptation via Soft Neighborhood Density

Saito, K., Kim, D., Teterwak, P., Sclaroff, S., Darrell, T., & Saenko, K. (2021) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv48922.2021.00905 · Cited by 44

Towards Domain Generalization for ECG and EEG Classification: Algorithms and Benchmarks

Ballas, A., & Diou, C. (2023) · IEEE Transactions on Emerging Topics in Computational Intelligence · doi:10.1109/tetci.2023.3306253 · Cited by 41

Stacked Robust Adaptively Regularized Auto-Regressions for Domain Adaptation

Jiang, W., Gao, H., Lu, W., Liu, W., Chung, F.-L., & Huang, H. (2018) · IEEE Transactions on Knowledge and Data Engineering · doi:10.1109/tkde.2018.2837085 · Cited by 34

Generalized Conditional Domain Adaptation: A Causal Perspective With Low-Rank Translators

Ren, C.-X., Xu, X., & Yan, H. (2018) · IEEE Transactions on Cybernetics · doi:10.1109/tcyb.2018.2874219 · Cited by 36

Sparse filtering based domain adaptation for mechanical fault diagnosis

Zhang, Z., Chen, H., Li, S., & An, Z. (2020) · Neurocomputing · doi:10.1016/j.neucom.2020.02.049 · Cited by 35

Comparing subject-to-subject transfer learning methods in surface electromyogram-based motion recognition with shallow and deep classifiers

Hoshino, T., Kanoga, S., Tsubaki, M., & Aoyama, A. (2022) · Neurocomputing · doi:10.1016/j.neucom.2021.12.081 · Cited by 35

Source-Free Video Domain Adaptation by Learning Temporal Consistency for Action Recognition

Xu, Y., Yang, J., Cao, H., Wu, K., Wu, M., & Chen, Z. (2022) · Lecture notes in computer science · doi:10.1007/978-3-031-19830-4_9 · Cited by 38

GAN-based data augmentation and pseudo-label refinement with holistic features for unsupervised domain adaptation person re-identification

Pham, D. H., Nguyen, A. D., & Nguyen, H. N. (2024) · Knowledge-Based Systems · doi:10.1016/j.knosys.2024.111471 · Cited by 34

Generative Adversarial Networks for Video-to-Video Domain Adaptation

Chen, J., Li, Y., Ma, K., & Zheng, Y. (2020) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v34i04.5750 · Cited by 34

Visual domain adaptation based on modified A− distance and sparse filtering

Han, C., Lei, Y., Xie, Y., Zhou, D., & Gong, M. (2020) · Pattern Recognition · doi:10.1016/j.patcog.2020.107254 · Cited by 35

Dynamic transfer soft sensor for concept drift adaptation

Zhang, T., Yan, G., Ren, M., Cheng, L., Li, R., & ., G. X. (2023) · Journal of Process Control · doi:10.1016/j.jprocont.2023.01.012 · Cited by 33

Data-balanced transformer for accelerated ionizable lipid nanoparticles screening in mRNA delivery

Wu, K., Yang, X., Wang, Z., Li, N., Zhang, J., & Liu, L. (2024) · Briefings in Bioinformatics · doi:10.1093/bib/bbae186 · Cited by 38

Building, benchmarking, and exploring perturbative maps of transcriptional and morphological data

Çelik, S., Hütter, J.-C., Carlos, S. M., Lazar, N. H., Mohan, R., Tillinghast, C. A., Biancalani, T., Fay, M. M., Earnshaw, B. A., & Haque, I. S. (2024) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1012463 · Cited by 40

A deep transfer learning model for online monitoring of surface roughness in milling with variable parameters

Zhou, K., Feng, P., Feng, F., Ma, H., Kang, N., & Wang, J. (2024) · Computers in Industry · doi:10.1016/j.compind.2024.104199 · Cited by 34

Feature Isolation for Hypothesis Testing in Retinal Imaging: An Ischemic Stroke Prediction Case Study

Lim, G., Lim, Z. W., Xu, D., Ting, D. S. W., Wong, T. Y., Lee, M. L., & Hsu, W. (2019) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v33i01.33019510 · Cited by 33

Hybrid adversarial network for unsupervised domain adaptation

Zhang, C., Zhao, Q., & Wang, Y. (2019) · Information Sciences · doi:10.1016/j.ins.2019.12.005 · Cited by 32

Robust and high-order correlation alignment for unsupervised domain adaptation

Cheng, Z., Chen, C., Chen, Z., Fang, K., & Jin, X. (2021) · Neural Computing and Applications · doi:10.1007/s00521-020-05465-7 · Cited by 35

Vision-Based Gesture Recognition in Human-Robot Teams Using Synthetic Data

de Melo, C. M., Rothrock, B., Gurram, P. K., Ulutan, O., & Manjunath, B. S. (2020) · IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) · doi:10.1109/iros45743.2020.9340728 · Cited by 33

Associative Domain AdaptationPreprint

Haeusser, P., Frerix, T., Mordvintsev, A., & Cremers, D. (2017) · arXiv (Cornell University) · doi:10.48550/arxiv.1708.00938 · Cited by 40

Data-Driven Modeling for Transferable Sea State Estimation Between Marine Systems

Cheng, X., Li, G., Han, P., Skulstad, R., Chen, S., & Zhang, H. (2021) · IEEE Transactions on Intelligent Transportation Systems · doi:10.1109/tits.2021.3129916 · Cited by 32

T-TIME: Test-Time Information Maximization Ensemble for Plug-and-Play BCIs

Li, S., Wang, Z., Luo, H., Ding, L., & Wu, D. (2023) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.2023.3303289 · Cited by 33

A novel deep transfer learning framework integrating general and domain-specific features for EEG-based brain–computer interface

Liang, Z., Zheng, Z., Chen, W., Pei, Z., Wang, J., & Chen, J. (2024) · Biomedical Signal Processing and Control · doi:10.1016/j.bspc.2024.106311 · Cited by 32

Anatomy-aware and acquisition-agnostic joint registration with SynthMorph

Hoffmann, M., Hoopes, A., Greve, D. N., Fischl, B. R., & Dalca, A. V. (2024) · Imaging Neuroscience · doi:10.1162/imag_a_00197 · Cited by 32

In2I: Unsupervised Multi-Image-to-Image Translation Using Generative Adversarial Networks

Perera, P., Abavisani, M., & Patel, V. M. (2018) · Proceedings - International Conference on Pattern Recognition/Proceedings/International Conference on Pattern Recognition · doi:10.1109/icpr.2018.8545464 · Cited by 32

Unsupervised Domain Adaptation by Mapped Correlation Alignment

Zhang, Y., Wang, N., Cai, S., & Song, L. (2018) · IEEE Access · doi:10.1109/access.2018.2865249 · Cited by 35

Inferring Latent Domains for Unsupervised Deep Domain Adaptation

Mancini, M., Porzi, L., Bulò, S. R., Barbara Caputo, B., & Ricci, E. (2019) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2019.2933829 · Cited by 34

On Robustness of Unsupervised Domain Adaptation for Speaker Recognition

Bousquet, P.-M., & Rouvier, M. (2019) · Interspeech (USB) · doi:10.21437/interspeech.2019-1524 · Cited by 32

A Kernelized Unified Framework for Domain Adaptation

Sanodiya, R. K., Mathew, J., Paul, B., & Jose, B. A. (2019) · IEEE Access · doi:10.1109/access.2019.2958736 · Cited by 32

Cross lingual speech emotion recognition via triple attentive asymmetric convolutional neural network

Ocquaye, E. N. N., Mao, Q., Xue, Y., & Song, H. (2020) · International Journal of Intelligent Systems · doi:10.1002/int.22291 · Cited by 30

InstanceEasyTL: An Improved Transfer-Learning Method for EEG-Based Cross-Subject Fatigue Detection

Zeng, H., Zhang, J., Zakaria, W., Babiloni, F., Borghini, G., Li, X., & Kong, W. (2020) · Sensors · doi:10.3390/s20247251 · Cited by 32

CoNMix for Source-free Single and Multi-target Domain Adaptation

Kumar, V., Lal, R., Patil, H., & Chakraborty, A. (2023) · IEEE Winter Conference on Applications of Computer Vision · doi:10.1109/wacv56688.2023.00416 · Cited by 32

Transferring Audio Deepfake Detection Capability across Languages

Ba, Z., Wen, Q., Cheng, P., Wang, Y., Lin, F., Lü, L., & Liu, Z. (2023) · International World Wide Web Conference (WWW) · doi:10.1145/3543507.3583222 · Cited by 32

Cross-database and cross-channel electrocardiogram arrhythmia heartbeat classification based on unsupervised domain adaptation

Imtiaz, M. N., & Khan, N. (2023) · Expert Systems with Applications · doi:10.1016/j.eswa.2023.122960 · Cited by 31

Uncertainty-aware pseudo-label filtering for source-free unsupervised domain adaptation

Chen, X., Yang, H., Zhang, H., Yao, H., & Zhu, X. (2023) · Neurocomputing · doi:10.1016/j.neucom.2023.127190 · Cited by 33

Effective Comparative Prototype Hashing for Unsupervised Domain Adaptation

Cui, H. J., Zhao, L., Li, F., Zhu, L., Han, X., & Li, J. (2024) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v38i8.28674 · Cited by 33

Spectral–Spatial Adversarial Multidomain Synthesis Network for Cross-Scene Hyperspectral Image Classification

Chen, X., Gao, L., Zhang, M., Chen, C., & Yan, S. (2024) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2024.3401231 · Cited by 33

Geotechnical risk modeling using an explainable transfer learning model incorporating physical guidance

Liu, F., Liu, W., Li, A., & Cheng, J. C. P. (2024) · Engineering Applications of Artificial Intelligence · doi:10.1016/j.engappai.2024.109127 · Cited by 31

Exploiting Images for Video Recognition: Heterogeneous Feature Augmentation via Symmetric Adversarial Learning

Yu, F., Wu, X., Chen, J., & Duan, L. (2019) · IEEE Transactions on Image Processing · doi:10.1109/tip.2019.2917867 · Cited by 30

Domain Adaptive Image-to-Image Translation

Chen, Y.-C., Xu, X., & Jia, J. (2020) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr42600.2020.00532 · Cited by 31

Generating Target Image-Label Pairs for Unsupervised Domain Adaptation

Li, R., Cao, W., Wu, S., & Wong, H. (2020) · IEEE Transactions on Image Processing · doi:10.1109/tip.2020.3009853 · Cited by 32

Optimal Transport Based Deep Domain Adaptation Approach for Fault Diagnosis of Rotating Machine

Liu, Z., Jiang, L.-B., Wei, H., Chen, L., & Li, X. (2021) · IEEE Transactions on Instrumentation and Measurement · doi:10.1109/tim.2021.3050173 · Cited by 31

Divergence Optimization for Noisy Universal Domain Adaptation

Yu, Q., Hashimoto, A., & Ushiku, Y. (2021) · Computer Vision and Pattern Recognition · doi:10.1109/cvpr46437.2021.00254 · Cited by 32

A Two-Way alignment approach for unsupervised multi-Source domain adaptation

Liu, Y., & Ren, C.-X. (2021) · Pattern Recognition · doi:10.1016/j.patcog.2021.108430 · Cited by 31

Adversarial style discrepancy minimization for unsupervised domain adaptation

Luo, X., Chen, W., Liang, Z., Li, C., & Tan, Y. (2022) · Neural Networks · doi:10.1016/j.neunet.2022.10.015 · Cited by 31

Domain Adaptive Algorithm Based on Multi-Manifold Embedded Distributed Alignment for Brain-Computer Interfaces

Gao, Y., Liu, Y., She, Q., & Zhang, J. (2022) · IEEE Journal of Biomedical and Health Informatics · doi:10.1109/jbhi.2022.3218453 · Cited by 30

Attention-Based Dynamic Alignment and Dynamic Distribution Adaptation for Remote Sensing Cross-Domain Scene Classification

Yang, C., Dong, Y., Du, B., & Zhang, L. (2022) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2022.3225589 · Cited by 31

Domain distribution variation learning via adversarial adaption for helicopter transmission system fault diagnosis

Sun, K., Yin, A., & Lu, S. (2024) · Mechanical Systems and Signal Processing · doi:10.1016/j.ymssp.2024.111419 · Cited by 31

Evolutionary Ensemble Learning for EEG-Based Cross-Subject Emotion Recognition

Zhang, H., Zuo, T., Chen, Z., Wang, X., & Sun, P. Z. H. (2024) · IEEE Journal of Biomedical and Health Informatics · doi:10.1109/jbhi.2024.3384816 · Cited by 30

Self-supervised domain adaptation for machinery remaining useful life prediction

Xuan, Q. L., Munderloh, M., & Östermann, J. (2024) · Reliability Engineering & System Safety · doi:10.1016/j.ress.2024.110296 · Cited by 32

Tracking Persons-of-Interest via Unsupervised Representation Adaptation

Zhang, S., Huang, J., Lim, J., Gong, Y., Wang, J., Ahuja, N., & Yang, M. (2019) · International Journal of Computer Vision · doi:10.1007/s11263-019-01212-1 · Cited by 31

Deep Learning Pitfall: Impact of Novel Ultrasound Equipment Introduction on Algorithm Performance and the Realities of Domain Adaptation

Blaivas, M., Blaivas, L. N., & Tsung, J. W. (2021) · Journal of Ultrasound in Medicine · doi:10.1002/jum.15765 · Cited by 30

Graph Embedding and Distribution Alignment for Domain Adaptation in Hyperspectral Image Classification

Huang, Y., Peng, J., Ning, Y., Sun, W., & Du, Q. (2021) · IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing · doi:10.1109/jstars.2021.3099805 · Cited by 30

Easy Domain Adaptation for cross-subject multi-view emotion recognition

Chen, C., Vong, C., Wang, S., Wang, H., & Pang, M. (2021) · Knowledge-Based Systems · doi:10.1016/j.knosys.2021.107982 · Cited by 30

Scarf enables a highly memory-efficient analysis of large-scale single-cell genomics data

Dhapola, P., Rodhe, J., Olofzon, R., Bonald, T., Erlandsson, E., Soneji, S., & Karlsson, G. (2022) · Nature Communications · doi:10.1038/s41467-022-32097-3 · Cited by 32

Contrastive domain adaptation with consistency match for automated pneumonia diagnosis

Feng, Y., Wang, Z., Xu, X., Wang, Y., Fu, H., Li, S., Zhen, L., Lei, X., Cui, Y., Sim, J. Z. T., et al. (2022) · Medical Image Analysis · doi:10.1016/j.media.2022.102664 · Cited by 31

A Multi-Source Transfer Joint Matching Method for Inter-Subject Motor Imagery Decoding

Wei, F., Xu, X., Jia, T., Zhang, D., & Wu, X. (2023) · IEEE Transactions on Neural Systems and Rehabilitation Engineering · doi:10.1109/tnsre.2023.3243257 · Cited by 31

Kernel adapted extreme learning machine for cross-domain fault diagnosis of aero-engines

Li, B., Xue, S.-K., Fu, Y.-H., Tang, Y., & Zhao, Y.-P. (2024) · Aerospace Science and Technology · doi:10.1016/j.ast.2024.108970 · Cited by 29

Online Boosting Adaptive Learning under Concept Drift for Multistream Classification

Yu, E., Jie Lu, B., Zhang, B., & Zhang, G. (2024) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v38i15.29590 · Cited by 29

Cross-Domain Visual Representations via Unsupervised Graph Alignment

Yang, B., & Yuen, P. C. (2019) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v33i01.33015613 · Cited by 28

Domain2Vec: Domain Embedding for Unsupervised Domain Adaptation

Peng, X., Li, Y., & Saenko, K. (2020) · Lecture notes in computer science · doi:10.1007/978-3-030-58539-6_45 · Cited by 32

Machine Learning for Fraud Detection in E-Commerce: A Research Agenda

Tax, N., de Vries, K. J., de Jong, M., Dosoula, N., van den Akker, B., Smith, J., Thuong, O., & Bernardi, L. (2021) · Communications in computer and information science · doi:10.1007/978-3-030-87839-9_2 · Cited by 39

Correlation Alignment for Unsupervised Domain Adaptation

Sun, B., Feng, J., & Saenko, K. (2017) · Advances in computer vision and pattern recognition · doi:10.1007/978-3-319-58347-1_8 · Cited by 423

Deep CORAL: Correlation Alignment for Deep Domain Adaptation

Sun, B., & Saenko, K. (2016) · Lecture Notes in Computer Science · doi:10.1007/978-3-319-49409-8_35 · Cited by 3,757

Unsupervised Domain Adaptation Using Approximate Label MatchingPreprint

Ash, J. T., Schapire, R. E., & Engelhardt, B. E. (2016) · arXiv (Cornell University) · doi:10.48550/arxiv.1602.04889 · Cited by 7

A simple approach for unsupervised domain adaptation

Guo, X., Chen, W., & Yin, J. (2016) · Proceedings - International Conference on Pattern Recognition/Proceedings/International Conference on Pattern Recognition · doi:10.1109/icpr.2016.7899860 · Cited by 7

Simple Domain Adaptation with Class Prediction Uncertainty Alignment.Preprint

Manders, J., Marchiori, E., & van Laarhoven, T. (2018) · arXiv (Cornell University) · Cited by 13