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

GA-DAN: Geometry-Aware Domain Adaptation Network for Scene Text Detection and Recognition

Zhan, F., Xue, C., & Lu, S. (2019) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2019.00920 · Cited by 93

Transfer learning for remaining useful life prediction based on consensus self-organizing models

Fan, Y., Nowaczyk, S., & Rognvaldsson, T. S. (2020) · Reliability Engineering & System Safety · doi:10.1016/j.ress.2020.107098 · Cited by 98

Deep Domain Adaptation for Non-Intrusive Load Monitoring Based on a Knowledge Transfer Learning Network

Lin, J., Ma, J., Zhu, J. G., & Liang, H. (2021) · IEEE Transactions on Smart Grid · doi:10.1109/tsg.2021.3115910 · Cited by 90

Bridging the Theoretical Bound and Deep Algorithms for Open Set Domain Adaptation

Li, Z., Fang, Z., Liu, F., Yuan, B., Zhang, G., & Lü, J. (2021) · IEEE Transactions on Neural Networks and Learning Systems · doi:10.1109/tnnls.2021.3119965 · Cited by 103

Time Series Domain Adaptation via Sparse Associative Structure Alignment

Cai, R., Chen, J., Li, Z., Chen, W., Zhang, K., Ye, J., Li, Z., Yang, X., & Zhang, Z. (2021) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v35i8.16846 · Cited by 90

Distant Supervised Centroid Shift: A Simple and Efficient Approach to Visual Domain Adaptation

Liang, J., He, R., Sun, Z., & Tan, T. (2019) · 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.2019.00309 · Cited by 88

Discriminative Transfer Feature and Label Consistency for Cross-Domain Image Classification

Li, S., Liu, C. H., Su, L., Xie, B., Ding, Z., Chen, C. L. P., & Wu, D. O. (2020) · IEEE Transactions on Neural Networks and Learning Systems · doi:10.1109/tnnls.2019.2958152 · Cited by 91

Cross-Dataset Activity Recognition via Adaptive Spatial-Temporal Transfer Learning

Qin, X., Chen, Y., Wang, J., & Yu, C. (2019) · Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies · doi:10.1145/3369818 · Cited by 90

Learning Invariant Representations and Risks for Semi-supervised Domain Adaptation

Li, B., Wang, Y., Zhang, S., Li, D., Keutzer, K., Darrell, T., & Zhao, H. (2021) · 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/cvpr46437.2021.00116 · Cited by 90

Cross-Domain Sentiment Classification with Target Domain Specific Information

Peng, M., Zhang, Q., Jiang, Y., & Huang, X. (2018) · Proceedings of the conference - Association for Computational Linguistics. Meeting · doi:10.18653/v1/p18-1233 · Cited by 88

A novel deep multi-source domain adaptation framework for bearing fault diagnosis based on feature-level and task-specific distribution alignment

Rezaeianjouybari, B., & Shang, Y. (2021) · Measurement · doi:10.1016/j.measurement.2021.109359 · Cited by 89

Are Labels Always Necessary for Classifier Accuracy Evaluation?

Deng, W., & Zheng, L. (2021) · 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/cvpr46437.2021.01482 · Cited by 98

Preventing dataset shift from breaking machine-learning biomarkers

Dockès, J., Varoquaux, G. P., & Poline, J. (2021) · GigaScience · doi:10.1093/gigascience/giab055 · Cited by 99

Joint feature synthesis and embedding: Adversarial cross-modal retrieval revisited

Xu, X., Lin, K., Yang, Y., Hanjalic, A., & Shen, H. T. (2022) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2020.3045530 · Cited by 88

When Unsupervised Domain Adaptation Meets Tensor Representations

Lü, H., Zhang, L., Cao, Z., Wei, W., Xian, K., Shen, C., & van den Hengel, A. (2017) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2017.72 · Cited by 83

Class-Aligned and Class-Balancing Generative Domain Adaptation for Hyperspectral Image Classification

Feng, J., Zhou, Z., Shang, R., Wu, J., Zhang, T., Zhang, X., & Jiao, L. (2024) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2024.3367765 · Cited by 86

Learning Linear Transformations for Fast Arbitrary Style TransferPreprint

Li, X., Liu, S., Kautz, J., & Yang, M. (2018) · arXiv (Cornell University) · doi:10.48550/arxiv.1808.04537 · Cited by 92

Recent Advances in Transfer Learning for Cross-Dataset Visual Recognition

Zhang, J., Li, W., Ogunbona, P., & Xu, D. (2019) · ACM Computing Surveys · doi:10.1145/3291124 · Cited by 135

Different Set Domain Adaptation for Brain-Computer Interfaces: A Label Alignment Approach

He, H., & Wu, D. (2020) · IEEE Transactions on Neural Systems and Rehabilitation Engineering · doi:10.1109/tnsre.2020.2980299 · Cited by 84

FedNILM: Applying Federated Learning to NILM Applications at the Edge

Zhang, Y., Tang, G., Huang, Q., Wang, Y., Wu, K., Yu, K., & Shao, X. (2022) · IEEE Transactions on Green Communications and Networking · doi:10.1109/tgcn.2022.3167392 · Cited by 85

Prompt-Based Distribution Alignment for Unsupervised Domain Adaptation

Bai, S., Zhang, M., Zhou, W., Huang, S., Luan, Z., Wang, D., & Chen, B. (2024) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v38i2.27830 · Cited by 88

Domain Adaptation Based on Correlation Subspace Dynamic Distribution Alignment for Remote Sensing Image Scene Classification

Zhang, J., Liu, J., Pan, B., & Shi, Z. (2020) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2020.2985072 · Cited by 84

Hyperspectral Imaging Combined With Deep Transfer Learning for Rice Disease Detection

Feng, L., Wu, B., He, Y., & Zhang, C. (2021) · Frontiers in Plant Science · doi:10.3389/fpls.2021.693521 · Cited by 89

Self-Supervised Autoregressive Domain Adaptation for Time Series Data

Ragab, M., Eldele, E., Chen, Z., Wu, M., Kwoh, C. K., & Li, X. (2022) · IEEE Transactions on Neural Networks and Learning Systems · doi:10.1109/tnnls.2022.3183252 · Cited by 86

Instance Level Affinity-Based Transfer for Unsupervised Domain Adaptation

Sharma, A., Kalluri, T., & Chandraker, M. (2021) · Computer Vision and Pattern Recognition · doi:10.1109/cvpr46437.2021.00532 · Cited by 53

On Minimum Discrepancy Estimation for Deep Domain Adaptation

Rahman, M. M., Fookes, C., Baktashmotlagh, M., & Sridharan, S. (2020) · Springer eBooks · doi:10.1007/978-3-030-30671-7_6 · Cited by 82

Deep Multi-Modality Adversarial Networks for Unsupervised Domain Adaptation

Ma, X., Zhang, T., & Xu, C. (2019) · IEEE Transactions on Multimedia · doi:10.1109/tmm.2019.2902100 · Cited by 80

Unsupervised Instance Segmentation in Microscopy Images via Panoptic Domain Adaptation and Task Re-Weighting

Liu, D., Zhang, D., Song, Y., Zhang, F., O’Donnell, L. J., Huang, H., Chen, M., & Cai, W. (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/cvpr42600.2020.00430 · Cited by 82

PDAM: A Panoptic-Level Feature Alignment Framework for Unsupervised Domain Adaptive Instance Segmentation in Microscopy Images

Liu, D., Zhang, D., Song, Y., Zhang, F., O’Donnell, L. J., Huang, H., Chen, M., & Cai, W. (2020) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2020.3023466 · Cited by 83

Landslide mapping based on a hybrid CNN-transformer network and deep transfer learning using remote sensing images with topographic and spectral features

Wu, L., Liu, R., Ju, N., Zhang, A., Gou, J., He, G., & Lei, Y. (2023) · International Journal of Applied Earth Observation and Geoinformation · doi:10.1016/j.jag.2023.103612 · Cited by 81

Domain adaptation for regression under Beer–Lambert’s law

Nikzad‐Langerodi, R., Zellinger, W., Saminger‐Platz, S., & Moser, B. (2020) · Knowledge-Based Systems · doi:10.1016/j.knosys.2020.106447 · Cited by 81

MADAN: Multi-source Adversarial Domain Aggregation Network for Domain Adaptation

Zhao, S., Li, B., Xu, P., Yue, X., Ding, G., & Keutzer, K. (2021) · International Journal of Computer Vision · doi:10.1007/s11263-021-01479-3 · Cited by 82

In Search of Lost Domain Generalization

Gulrajani, I., & Lopez-Paz, D. (2020) · arXiv · doi:10.48550/arxiv.2007.01434 · Cited by 440

Personalized Human Activity Recognition Based on Integrated Wearable Sensor and Transfer Learning

Fu, Z., He, X., Wang, E., Huo, J., Huang, J., & Wu, D. (2021) · Sensors · doi:10.3390/s21030885 · Cited by 79

Domain Adaptation by Class Centroid Matching and Local Manifold Self-Learning

Tian, L., Tang, Y., Hu, L., Ren, Z., & Zhang, W. (2020) · IEEE Transactions on Image Processing · doi:10.1109/tip.2020.3031220 · Cited by 79

Uncertainty-aware consistency regularization for cross-domain semantic segmentation

Zhou, Q., Feng, Z., Gu, Q., Cheng, G., Lu, X., Shi, J., & Ma, L. (2022) · Computer Vision and Image Understanding · doi:10.1016/j.cviu.2022.103448 · Cited by 92

Attention-Based Multi-Source Domain Adaptation

Zuo, Y., Yao, H., & Xu, C. (2021) · IEEE Transactions on Image Processing · doi:10.1109/tip.2021.3065254 · Cited by 84

A novel transfer learning fault diagnosis method based on Manifold Embedded Distribution Alignment with a little labeled data

Zhao, K., Jiang, H., Wu, Z., & Lu, T. (2020) · Journal of Intelligent Manufacturing · doi:10.1007/s10845-020-01657-z · Cited by 77

Deep Hashing Network for Unsupervised Domain Adaptation

Ramakrishnan, R., Nagabandi, B., Eusébio, J., Chakraborty, S., Venkateswara, H., & Panchanathan, S. (2020) · Springer eBooks · doi:10.1007/978-3-030-45529-3_4 · Cited by 101

Cross-Entropy Adversarial View Adaptation for Person Re-identification

Wu, L. Y., Hong, R., Wang, Y., & Wang, M. (2019) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2019.2909549 · Cited by 79

An Intelligent Fault Diagnosis Method Based on Domain Adaptation and Its Application for Bearings Under Polytropic Working Conditions

Lei, Z., Wen, G., Dong, S., Huang, X., Zhou, H., Zhang, Z., & Chen, X. (2020) · IEEE Transactions on Instrumentation and Measurement · doi:10.1109/tim.2020.3041105 · Cited by 77

Probabilistic Harmonization and Annotation of Single-cell Transcriptomics Data with Deep Generative ModelsPreprint

Xu, C. A., Lopez, R., Mehlman, E., Regier, J., Jordan, M. I., & Yosef, N. (2019) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/532895 · Cited by 80

A Little Data Goes a Long Way: Automating Seismic Phase Arrival Picking at Nabro Volcano With Transfer Learning

Lapins, S., Goitom, B., Kendall, J. M., Werner, M. J., Cashman, K. V., & Hammond, J. O. S. (2021) · Journal of Geophysical Research Solid Earth · doi:10.1029/2021jb021910 · Cited by 79

Webly Supervised Learning Meets Zero-shot Learning: A Hybrid Approach for Fine-Grained Classification

Niu, L., Veeraraghavan, A., & Sabharwal, A. (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.2018.00749 · Cited by 76

Unifying Unsupervised Domain Adaptation and Zero-Shot Visual Recognition

Wang, Q., Bu, P., & Breckon, T. P. (2019) · International Joint Conference on Neural Networks (IJCNN) · doi:10.1109/ijcnn.2019.8852015 · Cited by 75

Bi-Directional Generation for Unsupervised Domain Adaptation

Yang, G., Xia, H., Ding, M., & Ding, Z. (2020) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v34i04.6137 · Cited by 74

A sparse domain adaption network for remaining useful life prediction of rolling bearings under different working conditions

Miao, M., Yu, J., & Zhao, Z. (2021) · Reliability Engineering & System Safety · doi:10.1016/j.ress.2021.108259 · Cited by 75

On the effects of data normalization for domain adaptation on EEG data

Apicella, A., Isgrò, F., Pollastro, A., & Prevete, R. (2023) · Engineering Applications of Artificial Intelligence · doi:10.1016/j.engappai.2023.106205 · Cited by 79

Curriculum self-paced learning for cross-domain object detection

Soviany, P., Ionescu, R. T., Rota, P., & Sebe, N. (2021) · Computer Vision and Image Understanding · doi:10.1016/j.cviu.2021.103166 · Cited by 75

Discriminative feature alignment: Improving transferability of unsupervised domain adaptation by Gaussian-guided latent alignment

王, J. 璟. W., Chen, J., Lin, J., Sigal, L., & de Silva, C. W. (2021) · Pattern Recognition · doi:10.1016/j.patcog.2021.107943 · Cited by 75

Discriminative Invariant Alignment for Unsupervised Domain Adaptation

Lu, Y., Li, D., Wang, W., Lai, Z., Zhou, J., & Li, X. (2021) · IEEE Transactions on Multimedia · doi:10.1109/tmm.2021.3073258 · Cited by 74

Unsupervised domain adaptation for crack detection

Weng, X., Huang, Y., Li, Y., Yang, H., & Yu, S. (2023) · Automation in Construction · doi:10.1016/j.autcon.2023.104939 · Cited by 73

Open-set domain adaptation for scene classification using multi-adversarial learning

Zheng, J.-P., Wen, Y., Chen, M.-X., Yuan, S., Li, W.-J., Zhao, Y., Wu, W.-Z., Zhang, L., Dong, R.-M., & Fu, H.-H. (2024) · Isprs Journal of Photogrammetry and Remote Sensing · doi:10.1016/j.isprsjprs.2024.01.015 · Cited by 81

A Method for Vehicle Detection in High-Resolution Satellite Images that Uses a Region-Based Object Detector and Unsupervised Domain Adaptation

Koga, Y., Miyazaki, H., & Shibasaki, R. (2020) · Remote Sensing · doi:10.3390/rs12030575 · Cited by 76

Deep Transfer Low-Rank Coding for Cross-Domain Learning

Ding, Z., & Fu, Y. (2018) · IEEE Transactions on Neural Networks and Learning Systems · doi:10.1109/tnnls.2018.2874567 · Cited by 72

Optimal Transport in Reproducing Kernel Hilbert Spaces: Theory and Applications

Zhang, Z., Wang, M., & Nehorai, A. (2019) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2019.2903050 · Cited by 72

Discriminative and Geometry-Aware Unsupervised Domain Adaptation

Luo, L., Chen, L., Hu, S., Lu, Y., & Wang, X. (2020) · IEEE Transactions on Cybernetics · doi:10.1109/tcyb.2019.2962000 · Cited by 73

The CORAL+ Algorithm for Unsupervised Domain Adaptation of PLDA

Lee, K. A., Wang, Q., & Koshinaka, T. (2019) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp.2019.8682852 · Cited by 72

Self Supervised Adversarial Domain Adaptation for Cross-Corpus and Cross-Language Speech Emotion Recognition

Latif, S., Rana, R. K., Khalifa, S., Jurdak, R., & Schuller, B. W. (2022) · IEEE Transactions on Affective Computing · doi:10.1109/taffc.2022.3167013 · Cited by 75

Unilateral alignment transfer neural network for fault diagnosis of aircraft engine

Li, B., Zhao, Y.-P., & Chen, Y.-B. (2021) · Aerospace Science and Technology · doi:10.1016/j.ast.2021.107031 · Cited by 70

Federated Domain Adaptation via Transformer for Multi-Site Alzheimer’s Disease Diagnosis

Lei, B., Zhu, Y., Liang, E., Yang, P., Chen, S., Hu, H., Xie, H., Wei, Z., Hao, F., Song, X., et al. (2023) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2023.3300725 · Cited by 73

Feature-based transfer learning for network security

Zhao, J., Shetty, S. S., & Pan, J. W. (2017) · IEEE Military Communications Conference (MILCOM) · doi:10.1109/milcom.2017.8170749 · Cited by 70

Multi-Component Image Translation for Deep Domain Generalization

Rahman, M. M., Fookes, C., Baktashmotlagh, M., & Sridharan, S. (2019) · IEEE Winter Conference on Applications of Computer Vision · doi:10.1109/wacv.2019.00067 · Cited by 69

AdaptSum: Towards Low-Resource Domain Adaptation for Abstractive Summarization

Yu, T., Liu, Z., & Fung, P. (2021) · Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL-HLT) · doi:10.18653/v1/2021.naacl-main.471 · Cited by 78

Learning Privacy Preserving Encodings Through Adversarial Training

Pittaluga, F., Koppal, S. J., & Chakrabarti, A. (2019) · IEEE Winter Conference on Applications of Computer Vision · doi:10.1109/wacv.2019.00089 · Cited by 70

A Game Theoretic Framework for Model Based Reinforcement LearningPreprint

Rajeswaran, A., Mordatch, I., & Kumar, V. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2004.07804 · Cited by 71

Domain Adaptive Faster R-CNN for Object Detection in the Wild

Chen, Y., Li, W., Sakaridis, C., Dai, D., & Gool, L. V. (2018) · Repository for Publications and Research Data (ETH Zurich) · doi:10.3929/ethz-b-000310976 · Cited by 67

Attribute-Identity Embedding and Self-Supervised Learning for Scalable Person Re-Identification

Li, H., Yan, S., Yu, Z., & Tao, D. (2019) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2019.2952550 · Cited by 67

Learning to See in the Dark with Events

Zhang, S., Zhang, Y., Jiang, Z., Zou, D., Ren, J., & Zhou, B. (2020) · Lecture notes in computer science · doi:10.1007/978-3-030-58523-5_39 · Cited by 66

Detecting Deficient Coverage in Colonoscopies

Freedman, D., Blau, Y., Katzir, L., Aides, A., Shimshoni, I., Veikherman, D., Golany, T., Gordon, A., Corrado, G. S., Matias, Y., et al. (2020) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2020.2994221 · Cited by 68

Joint EEG Feature Transfer and Semisupervised Cross-Subject Emotion Recognition

Peng, Y. K., Liu, H., Kong, W., Nie, F., Lu, B., & Cichocki, A. S. (2022) · IEEE Transactions on Industrial Informatics · doi:10.1109/tii.2022.3217120 · Cited by 65

Knowledge transfer in evolutionary multi-task optimization: A survey

Tan, Z., Luo, L., & Zhong, J. (2023) · Applied Soft Computing · doi:10.1016/j.asoc.2023.110182 · Cited by 65

PromptStyler: Prompt-driven Style Generation for Source-free Domain Generalization

Cho, J., Nam, G., Kim, S., Yang, H., & Kwak, S. (2023) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv51070.2023.01439 · Cited by 72

New domain adaptation method in shallow and deep layers of the CNN for bearing fault diagnosis under different working conditions

Jin, T., Yan, C., Chen, C., Yang, Z., Tian, H., & Guo, J. (2021) · The International Journal of Advanced Manufacturing Technology · doi:10.1007/s00170-021-07385-9 · Cited by 67

Dynamic Multiobjective Evolutionary Optimization via Knowledge Transfer and Maintenance

Lin, Q., Ye, Y., Ma, L., Jiang, M., & Tan, K. C. (2023) · IEEE Transactions on Systems Man and Cybernetics Systems · doi:10.1109/tsmc.2023.3322718 · Cited by 63

Heterogeneous defect prediction with two-stage ensemble learning

Li, Z., Jing, X., Zhu, X., Zhang, H., Xu, B., & Ying, S. (2019) · Automated Software Engineering · doi:10.1007/s10515-019-00259-1 · Cited by 63

Siamese-GAN: Learning Invariant Representations for Aerial Vehicle Image Categorization

Bashmal, L., Bazi, Y., AlHichri, H., AlRahhal, M., Ammour, N., & Alajlan, N. (2018) · Remote Sensing · doi:10.3390/rs10020351 · Cited by 60

Sample-to-sample correspondence for unsupervised domain adaptation

Das, D., & Lee, C. S. G. (2018) · Engineering Applications of Artificial Intelligence · doi:10.1016/j.engappai.2018.05.001 · Cited by 65

Embracing the disharmony in medical imaging: A Simple and effective framework for domain adaptation

Wang, R., Chaudhari, P., & Davatzikos, C. A. (2021) · Medical Image Analysis · doi:10.1016/j.media.2021.102309 · Cited by 69

Unsupervised person re-identification via multi-domain joint learning

Chen, F., Wang, N., Tang, J., Yan, P., & Yu, J. (2023) · Pattern Recognition · doi:10.1016/j.patcog.2023.109369 · Cited by 62

Contrastive Learning Based on Category Matching for Domain Adaptation in Hyperspectral Image Classification

Ning, Y., Peng, J., Liu, Q., Huang, Y., Sun, W., & Du, Q. (2023) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2023.3295357 · Cited by 62

Deep Dynamic Adaptation Network Based on Joint Correlation Alignment for Cross-Scene Hyperspectral Image Classification

Li, C., Sun, W., Peng, J., & Ren, K. (2023) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2023.3336197 · Cited by 63

Mind the Gap: Multilevel Unsupervised Domain Adaptation for Cross-Scene Hyperspectral Image Classification

Cai, M., Xi, B., Li, J., Feng, S., Li, Y., Li, Z., & Chanussot, J. (2024) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2024.3407952 · Cited by 62

Conditional Bures Metric for Domain Adaptation

Luo, Y.-W., & Ren, C.-X. (2021) · 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/cvpr46437.2021.01377 · Cited by 62

The Eyes of the Gods: A Survey of Unsupervised Domain Adaptation Methods Based on Remote Sensing Data

Xu, M., Wu, M., Chen, K., Zhang, C., & Guo, J. H. (2022) · Remote Sensing · doi:10.3390/rs14174380 · Cited by 61

Domain Adaptation by Joint Distribution Invariant Projections

Chen, S., Harandi, M. T., Jin, X., & Yang, X. (2020) · IEEE Transactions on Image Processing · doi:10.1109/tip.2020.3013167 · Cited by 61

Unsupervised Domain Adaptation Using Robust Class-Wise Matching

Lei Zhang, A., Wang, P., Wei, W., Lü, H., Shen, C., van den Hengel, A., & Zhang, Y. (2018) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2018.2842206 · Cited by 60

Attention-Based Multiscale Residual Adaptation Network for Cross-Scene Classification

Zhu, S., Du, B., Zhang, L., & Li, X. (2021) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2021.3056624 · Cited by 62

Cross-Subject Emotion Recognition Based on Domain Similarity of EEG Signal Transfer Learning

Ma, Y., Zhao, W., Meng, M., Zhang, Q., She, Q., & Zhang, J. (2023) · IEEE Transactions on Neural Systems and Rehabilitation Engineering · doi:10.1109/tnsre.2023.3236687 · Cited by 60

Toward Label-Efficient Emotion and Sentiment Analysis

Zhao, S., Hong, X., Yang, J., Zhao, Y., & Ding, G. (2023) · Proceedings of the IEEE · doi:10.1109/jproc.2023.3309299 · Cited by 62

Cross-domain activity recognition via substructural optimal transport

Wang, L., Chen, Y., Wang, J., & Qin, X. (2021) · Neurocomputing · doi:10.1016/j.neucom.2021.04.124 · Cited by 59

A Deep Domain Adaptative Network for Remaining Useful Life Prediction of Machines Under Different Working Conditions and Fault Modes

Miao, M., & Yu, J. (2021) · IEEE Transactions on Instrumentation and Measurement · doi:10.1109/tim.2021.3084305 · Cited by 59

Effective transfer learning of defect detection for photovoltaic module cells in electroluminescence images

Xie, X., Lai, G., You, M., Liang, J., & Leng, B. (2023) · Solar Energy · doi:10.1016/j.solener.2022.10.055 · Cited by 60

Asymmetric Adaptation of Deep Features for Cross-Domain Classification in Remote Sensing Imagery

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