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

An Efficient Deep Unsupervised Domain Adaptation for Unknown Malware Detection

Wang, F., Chai, G., Li, Q., & Wang, C. (2022) · Symmetry · doi:10.3390/sym14020296 · Cited by 13

Cycle-reconstructive subspace learning with class discriminability for unsupervised domain adaptation

Xu, Y., & Yan, H. (2022) · Pattern Recognition · doi:10.1016/j.patcog.2022.108700 · Cited by 13

Domain-Prior-Induced Structural MRI Adaptation for Clinical Progression Prediction of Subjective Cognitive Decline

Yu, M., Guan, H., Fang, Y., Yue, L., & Liu, M. (2022) · Lecture notes in computer science · doi:10.1007/978-3-031-16431-6_3 · Cited by 13

Subdomain adaptation network with category isolation strategy for tire defect detection

Zhang, Y., Wang, Y., Jiang, Z., Li, Z., Chen, J., & Lu, J. (2022) · Measurement · doi:10.1016/j.measurement.2022.112046 · Cited by 13

Visual Domain Adaptation through Locality Information

Devika, A. K., Sanodiya, R. K., Jose, B. R., & Mathew, J. (2023) · Engineering Applications of Artificial Intelligence · doi:10.1016/j.engappai.2023.106172 · Cited by 13

Rolling bearing fault diagnosis under time-varying speeds based on time-characteristic order spectrum and multi-scale domain adaptation network

Xu, Z., Tang, G., Pang, B., & Qi, X. (2023) · Measurement Science and Technology · doi:10.1088/1361-6501/acf332 · Cited by 13

Exploiting Images for Video Recognition with Hierarchical Generative Adversarial Networks

Yu, F., Wu, X., Sun, Y., & Duan, L. (2018) · International Joint Conference on Artificial Intelligence · doi:10.24963/ijcai.2018/154 · Cited by 13

Deep domain adaptation with manifold aligned label transfer

Minnehan, B., & Savakis, A. E. (2019) · Machine Vision and Applications · doi:10.1007/s00138-019-01003-1 · Cited by 12

Deep multi-Wasserstein unsupervised domain adaptation

Le, T.-N., Habrard, A., & Sebban, M. (2019) · Pattern Recognition Letters · doi:10.1016/j.patrec.2019.04.025 · Cited by 16

Ideal Regularized Discriminative Multiple Kernel Subspace Alignment for Domain Adaptation in Hyperspectral Image Classification

Yang, W., Peng, J., & Sun, W. (2020) · IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing · doi:10.1109/jstars.2020.3026316 · Cited by 13

Manifold embedded distribution adaptation for cross‐project defect prediction

Sun, Y., Jing, X., Wu, F., & Sun, Y. (2020) · IET Software · doi:10.1049/iet-sen.2019.0389 · Cited by 13

Limitations of Post-Hoc Feature Alignment for Robustness

Burns, C., & Steinhardt, J. (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/cvpr46437.2021.00255 · Cited by 13

A surface roughness grade recognition model for milled workpieces based on deep transfer learning

Su, J., Yi, H., Ling, L., Wang, S., Jiao, Y., & Niu, Y. (2021) · Measurement Science and Technology · doi:10.1088/1361-6501/ac3f86 · Cited by 13

Predicting Email and Article Clickthroughs with Domain-adaptive Language Models

Jaidka, K., Goyal, T., & Chhaya, N. (2018) · ACM Web Science Conference (WebSci) · doi:10.1145/3201064.3201071 · Cited by 14

Incorporating knowledge of plates in batch normalization improves generalization of deep learning for microscopy imagesPreprint

Lin, A., & Lu, A. X. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.10.14.512286 · Cited by 13

3D bridge segmentation using semi-supervised domain adaptation

Kellner, M., König, T., Jäkel, J., Klemt‐Albert, K., & Reiterer, A. (2025) · Automation in Construction · doi:10.1016/j.autcon.2025.106021 · Cited by 12

Heterogeneous domain adaptation and equipment matching: DANN-based Alignment with Cyclic Supervision (DBACS)

Gentner, N., & Susto, G. A. (2023) · Computers & Industrial Engineering · doi:10.1016/j.cie.2023.109821 · Cited by 12

Deep Transfer Learning-Based Detection for Flash Memory Channels

Mei, Z., Cai, K., Shi, L. X., Li, J., Chen, L., & Immink, K. A. S. (2024) · IEEE Transactions on Communications · doi:10.1109/tcomm.2024.3357616 · Cited by 12

Domain Adaptive LiDAR Point Cloud Segmentation via Density-Aware Self-Training

Xiao, A., Huang, J., Liu, K., Guan, D., Zhang, X., & Lu, S. (2024) · IEEE Transactions on Intelligent Transportation Systems · doi:10.1109/tits.2024.3386865 · Cited by 12

Graph correlated discriminant embedding for multi-source domain adaptation

Wong, W. K., Lu, Y., Lai, Z., & Li, X. (2024) · Pattern Recognition · doi:10.1016/j.patcog.2024.110538 · Cited by 12

Multi-source transfer learning via optimal transport feature ranking for EEG classification

Li, J., She, Q., Fang, F. Z., Chen, Y., & Zhang, Y. (2024) · Neurocomputing · doi:10.1016/j.neucom.2024.127944 · Cited by 13

Multi-source-free Domain Adaptive Object Detection

Zhao, S., Yao, H., Lin, C., Gao, Y., & Ding, G. (2024) · International Journal of Computer Vision · doi:10.1007/s11263-024-02170-z · Cited by 16

A Physics-Informed Deep Neural Network for Harmonization of CT Images

Zarei, M., Sotoudeh‐Paima, S., McCabe, C., Abadi, E., & Samei, E. (2024) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.2024.3428399 · Cited by 12

Pulling Target to Source: A New Perspective on Domain Adaptive Semantic Segmentation

Wang, H., Shen, Y., Fei, J., Li, W., Wu, L., Wang, Y., & Zhang, Z. (2024) · International Journal of Computer Vision · doi:10.1007/s11263-024-02285-3 · Cited by 12

Deep Contrastive Transfer Learning for Rotating Machinery Fault Diagnosis

Zhu, P., Ma, S., Han, Q., & Chu, F. (2024) · IEEE Transactions on Instrumentation and Measurement · doi:10.1109/tim.2024.3502723 · Cited by 12

Simulations of Common Unsupervised Domain Adaptation Algorithms for Image Classification

Chaddad, A., Wu, Y., Jiang, Y., Bouridane, A., & Desrosiers, C. (2025) · IEEE Transactions on Instrumentation and Measurement · doi:10.1109/tim.2025.3527531 · Cited by 12

Deep Transfer Learning With Generalized Distribution Matching Measure for Rotating Machinery Fault Diagnosis

Zhu, P., Ma, S., Han, Q., & Chu, F. (2025) · IEEE Transactions on Industrial Informatics · doi:10.1109/tii.2025.3529924 · Cited by 12

CRRL: Contrastive Region Relevance Learning Framework for Cross-city Traffic Prediction

Dai, G., Yi, W., Cao, J., Gong, Z., Fu, X., & Zhang, B. (2025) · Information Fusion · doi:10.1016/j.inffus.2025.103215 · Cited by 12

Class-Specific Reconstruction Transfer Learning via Sparse Low-Rank Constraint

Wang, S., Zhang, L., & Zuo, W. (2017) · IEEE International Conference on Computer Vision Workshops · doi:10.1109/iccvw.2017.116 · Cited by 12

Assessment of Domain Adaptation Approaches for QoT Estimation in Optical Networks

di Marino, R., Rottondi, C., Giusti, A., & Bianco, A. G. (2020) · Optical Fiber Communication Conference · doi:10.1364/ofc.2020.th3d.2 · Cited by 12

On Embodied Visual Navigation in Real Environments Through Habitat

Rosano, M., Furnari, A., Gulino, L., & Farinella, G. M. (2021) · Proceedings - International Conference on Pattern Recognition/Proceedings/International Conference on Pattern Recognition · doi:10.1109/icpr48806.2021.9413026 · Cited by 12

Efficient Identification of Critical Faults in Memristor-Based Inferencing Accelerators

Chen, C.-Y., & Chakrabarty, K. (2021) · IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems · doi:10.1109/tcad.2021.3102894 · Cited by 13

Transfer Learning for the Riemannian Tangent Space: Applications to Brain-Computer Interfaces

Bleuzé, A., Mattout, J., & Congedo, M. (2021) · International Conference on Engineering and Emerging Technologies (ICEET) · doi:10.1109/iceet53442.2021.9659607 · Cited by 11

The interaction of normalisation and clustering in sub-domain definition for multi-source transfer learning based time series anomaly detection

Nicholson, M., Agrahari, R., Conran, C., Assem, H., & Kelleher, J. D. (2022) · Knowledge-Based Systems · doi:10.1016/j.knosys.2022.109894 · Cited by 12

Analyzing Language-Independent Speaker Anonymization Framework under Unseen Conditions

Miao, X., Wang, X., Cooper, E., Yamagishi, J., & Tomashenko, N. (2022) · Interspeech (USB) · doi:10.21437/interspeech.2022-11065 · Cited by 12

Attention Regularized Laplace Graph for Domain Adaptation

Luo, L., Chen, L., & Hu, S. (2022) · IEEE Transactions on Image Processing · doi:10.1109/tip.2022.3216781 · Cited by 12

Cross-domain decision making based on criterion weights and risk attitudes for the diagnosis of breast lesions

Fu, C., Wu, Z., Chang, W., & Lin, M. (2023) · Artificial Intelligence Review · doi:10.1007/s10462-023-10394-7 · Cited by 12

Unsupervised domain adaptation for Covid-19 classification based on balanced slice Wasserstein distance

Gu, J., Qian, X., Zhang, Q., Zhang, H., & Wu, F. (2023) · Computers in Biology and Medicine · doi:10.1016/j.compbiomed.2023.107207 · Cited by 12

Discrepancy-Based Networks for Unsupervised Domain Adaptation: A Comparative Study

Csurka, G., Baradel, F., Chidlovskii, B., & Clinchant, S. (2017) · IEEE International Conference on Computer Vision Workshops · doi:10.1109/iccvw.2017.312 · Cited by 12

Iterative unsupervised domain adaptation for generalized cell detection from brightfield z-stacks

Liimatainen, K., Kananen, L., Latonen, L., & Ruusuvuori, P. (2019) · BMC Bioinformatics · doi:10.1186/s12859-019-2605-z · Cited by 12

Min-Max Statistical Alignment for Transfer Learning

Herath, S., Harandi, M. T., Fernando, B., & Nock, R. (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.2019.00951 · Cited by 12

Deep Domain Adaptation for Regression

Singh, A., & Chakraborty, S. (2019) · Studies in computational intelligence · doi:10.1007/978-3-030-31764-5_4 · Cited by 12

Unsupervised Domain Adaptation via Discriminative Classes-Center Feature Learning in Adversarial Network

Chen, W., & Hu, H. (2020) · Neural Processing Letters · doi:10.1007/s11063-020-10266-z · Cited by 12

Adversarial sliced Wasserstein domain adaptation networks

Zhang, Y., Wang, N., & Cai, S. (2020) · Image and Vision Computing · doi:10.1016/j.imavis.2020.103974 · Cited by 12

Unifying Top–Down Views by Task-Specific Domain Adaptation

Lin, J., Yu, T., Mou, L., Zhu, X. X., Ward, R. K., & Wang, Z. J. (2020) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2020.3022608 · Cited by 12

A Health Data Map-Based Ensemble of Deep Domain Adaptation Under Inhomogeneous Operating Conditions for Fault Diagnosis of a Planetary Gearbox

Ha, J. M., & Youn, B. D. (2021) · IEEE Access · doi:10.1109/access.2021.3083804 · Cited by 12

TWINs: Two Weighted Inconsistency-reduced Networks for Partial Domain AdaptationPreprint

Matsuura, T., Saito, K., & Harada, T. (2018) · arXiv (Cornell University) · doi:10.48550/arxiv.1812.07405 · Cited by 15

Unsupervised Domain Adaption of Object Detectors: A SurveyPreprint

Oza, P., Sindagi, V. A., Vibashan, V. S., & Patel, V. M. (2021) · arXiv (Cornell University) · Cited by 12

Adaptive Modeling of Fixed-Bed Reactors with Multicycle and Multimode Characteristics Based on Transfer Learning and Just-In-Time Learning

Guo, J., Du, W., & Naşcu, I. (2020) · Industrial & Engineering Chemistry Research · doi:10.1021/acs.iecr.9b06668 · Cited by 11

Transfer learning strategy for data-driven correction of wind measurement around buildings using cup anemometers

Li, R., Kikumoto, H., Jia, H., & Okaze, T. (2023) · Building and Environment · doi:10.1016/j.buildenv.2023.110499 · Cited by 11

DSDAN: Dual-Step Domain Adaptation Network Based on Bidirectional Knowledge Distillation for Cross-User Myoelectric Pattern Recognition

Lin, X., Zhang, X., Zhang, X., Chen, X. '., & Chen, X. (2023) · IEEE Sensors Journal · doi:10.1109/jsen.2023.3305619 · Cited by 12

Multi-Domain Adaptation for Motion Deblurring

Zhuang, K., Li, Q., Yuan, Y., & Wang, Q. (2023) · IEEE Transactions on Multimedia · doi:10.1109/tmm.2023.3314154 · Cited by 11

Unsupervised Transfer Learning Approach With Adaptive Reweighting and Resampling Strategy for Inter-Subject EOG-Based Gaze Angle Estimation

Zeng, Z., Tao, L., Su, R., Zhu, Y., Meng, L., Tuheti, A., Huang, H., Shu, F., Chen, W., & Chen, C. (2023) · IEEE Journal of Biomedical and Health Informatics · doi:10.1109/jbhi.2023.3330192 · Cited by 12

Subdomain adaptation via correlation alignment with entropy minimization for unsupervised domain adaptation

Gilo, O., Mathew, J., Mondal, S., & Sandoniya, R. K. (2024) · Pattern Analysis and Applications · doi:10.1007/s10044-024-01232-9 · Cited by 11

D3GU: Multi-target Active Domain Adaptation via Enhancing Domain Alignment

Zhang, L., Xu, L., Motamed, S., Chakraborty, S., & de la Torre, F. N. (2024) · IEEE Winter Conference on Applications of Computer Vision · doi:10.1109/wacv57701.2024.00256 · Cited by 11

Riemannian Locality Preserving Method for Transfer Learning With Applications on Brain-Computer Interface

Xu, G., Wang, Z., Hu, H., Zhao, X., Li, R., Zhou, T., & Xu, T. (2024) · IEEE Journal of Biomedical and Health Informatics · doi:10.1109/jbhi.2024.3402324 · Cited by 11

StyleAM: Perception-Oriented Unsupervised Domain Adaption for No-Reference Image Quality Assessment

Lu, Y., Li, X., Liu, J., & Chen, Z. (2024) · IEEE Transactions on Multimedia · doi:10.1109/tmm.2024.3521705 · Cited by 17

Unsupervised domain adaptation teacher–student network for retinal vessel segmentation via full-resolution refined model

Yue, K., Zhan, L., & Wang, Z. (2025) · Scientific Reports · doi:10.1038/s41598-024-83018-x · Cited by 11

Texture and noise dual adaptation for infrared image super-resolution

Huang, Y., Miyazaki, T., Liu, X., Dong, Y., & Omachi, S. (2025) · Pattern Recognition · doi:10.1016/j.patcog.2025.111449 · Cited by 11

SVIADF: Small Vessel Identification and Anomaly Detection Based on Wide-Area Remote Sensing Imagery and AIS Data Fusion

Chen, L., Hu, Z., Chen, J., & Sun, Y. (2025) · Remote Sensing · doi:10.3390/rs17050868 · Cited by 12

Object detection based on semi-supervised domain adaptation for imbalanced domain resources

Li, W., Wang, M., Wang, H., & Zhang, Y. (2020) · Machine Vision and Applications · doi:10.1007/s00138-020-01068-3 · Cited by 11

Domain Adversarial Fine-Tuning as an Effective Regularizer

Vernikos, G., Margatina, K., Chronopoulou, A., & Androutsopoulos, I. (2020) · Findings of the Association for Computational Linguistics: EMNLP (Findings of EMNLP) · doi:10.18653/v1/2020.findings-emnlp.278 · Cited by 11

Auxiliary task guided mean and covariance alignment network for adversarial domain adaptation

Qiang, W., Li, J., Zheng, C., & Su, B. (2021) · Knowledge-Based Systems · doi:10.1016/j.knosys.2021.107066 · Cited by 11

AutoEval: Are Labels Always Necessary for Classifier Accuracy Evaluation?

Deng, W., & Zheng, L. (2021) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2021.3136244 · Cited by 13

Multi-source domain adaptation of social media data for disaster management

Khattar, A., & Quadri, S. M. K. (2022) · Multimedia Tools and Applications · doi:10.1007/s11042-022-13456-0 · Cited by 11

Automatic Modulation Classification Based on CNN and Multiple Kernel Maximum Mean Discrepancy

Wang, N., Liu, Y., Ma, L., Yang, Y., & Wang, H. (2022) · Electronics · doi:10.3390/electronics12010066 · Cited by 11

Fault Diagnosis in Industrial Control Networks Using Transferability-Measured Adversarial Adaptation Network

Han, G., Xu, Z., Chen, C., Liu, L., & Zhu, H. (2022) · IEEE Transactions on Network and Service Management · doi:10.1109/tnsm.2022.3225428 · Cited by 11

A Polarimetric Scattering Characteristics-Guided Adversarial Learning Approach for Unsupervised PolSAR Image Classification

Dong, H., Si, L., Qiang, W., Miao, W., Zheng, C., Wu, Y., & Zhang, L. (2023) · Remote Sensing · doi:10.3390/rs15071782 · Cited by 12

Improving molecular representation learning with metric learning-enhanced optimal transport

Wu, F., Courty, N., Jin, S., & Li, S. Z. (2023) · Patterns · doi:10.1016/j.patter.2023.100714 · Cited by 13

Transferable adversarial masked self-distillation for unsupervised domain adaptation

Xia, Y., Yun, L., & Yang, C. (2023) · Complex & Intelligent Systems · doi:10.1007/s40747-023-01094-4 · Cited by 11

Causal Feature Selection in the Presence of Sample Selection Bias

Yang, S., Guo, X., Yu, K., Huang, X., Jiang, T., He, J., & Gu, L. (2023) · ACM Transactions on Intelligent Systems and Technology · doi:10.1145/3604809 · Cited by 12

Generalized Domain Adaptation Framework for Parametric Back-End in Speaker Recognition

Wang, Q., Okabe, K., Lee, K. A., & Koshinaka, T. (2023) · IEEE Transactions on Information Forensics and Security · doi:10.1109/tifs.2023.3287733 · Cited by 11

Progressive Fourier Adversarial Domain Adaptation for Object Classification and Retrieval

Li, T.-B., Su, Y.-T., Song, D., Li, W., Wei, Z., & Liu, A.-A. (2023) · IEEE Transactions on Multimedia · doi:10.1109/tmm.2023.3323862 · Cited by 12

Adversarial Domain Adaptation Being Aware of Class Relationships

Wang, Z., Jing, B., Ni, Y., Nanqing, D., Pengtao, X., & Xing, E. P. (2020) · Frontiers in artificial intelligence and applications · doi:10.3233/faia200267 · Cited by 12

TCANet for Domain Adaptation of Hyperspectral Images

Garea, A. S., Heras, D. B., & Argüello, F. (2019) · Remote Sensing · doi:10.3390/rs11192289 · Cited by 11

Capsule Network With Identifying Transferable Knowledge for Cross-Domain Sentiment Classification

Yin, H., Liu, P., Zhu, Z., Li, W., & Wang, Q. (2019) · IEEE Access · doi:10.1109/access.2019.2948628 · Cited by 12

Frustratingly Easy Personalization for Real-time Affect Interpretation of Facial Expression

Spaulding, S., & Breazeal, C. (2019) · International Conference on Affective Computing and Intelligent Interaction and workshops · doi:10.1109/acii.2019.8925515 · Cited by 12

Domain-Invariant Regression Under Beer-Lambert's Law

Nikzad‐Langerodi, R., Zellinger, W., Saminger‐Platz, S., & Moser, B. (2019) · International Conference on Machine Learning and Applications · doi:10.1109/icmla.2019.00108 · Cited by 11

Unsupervised urban scene segmentation via domain adaptation

Gao, L., Zhang, Y., Zou, F., Shao, J., & Lai, J. (2020) · Neurocomputing · doi:10.1016/j.neucom.2020.01.117 · Cited by 11

Enhancing unsupervised domain adaptation by discriminative relevance regularization

Zhang, W., Zhang, X., Lan, L., & Luo, Z. (2020) · Knowledge and Information Systems · doi:10.1007/s10115-020-01466-z · Cited by 11

Kernelized Unified Domain Adaptation on Geometrical Manifolds

Sanodiya, R. K., Mathew, J., Aditya, R., Jacob, A., & Nayanar, B. (2020) · Expert Systems with Applications · doi:10.1016/j.eswa.2020.114078 · Cited by 11

Cut-and-Paste Dataset Generation for Balancing Domain Gaps in Object Instance Detection

Yun, W., Kim, T., Lee, J., Kim, J., & Kim, J. (2021) · IEEE Access · doi:10.1109/access.2021.3051964 · Cited by 12

TransBoost: A Boosting-Tree Kernel Transfer Learning Algorithm for Improving Financial Inclusion

Sun, Y., Lu, T., Wang, C., Li, Y., Fu, H., Dong, J., & Xu, Y. (2022) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v36i11.21478 · Cited by 11

A novel forget-update module for few-shot domain generalization

Yuan, M., Cai, C., Lü, T., Wu, Y., Xu, Q., & Zhou, S. (2022) · Pattern Recognition · doi:10.1016/j.patcog.2022.108704 · Cited by 11

Teacher–Student Mutual Learning for efficient source-free unsupervised domain adaptation

Li, W., Fan, K., & Yang, H. (2022) · Knowledge-Based Systems · doi:10.1016/j.knosys.2022.110204 · Cited by 11

Cross-platform privacy-preserving CT image COVID-19 diagnosis based on source-free domain adaptation

Feng, Y., Luo, Y., & Yang, J. (2023) · Knowledge-Based Systems · doi:10.1016/j.knosys.2023.110324 · Cited by 11

Self-training adversarial learning for cross-domain retinal OCT fluid segmentation

Li, X., Niu, S., Gao, X., Zhou, X., Dong, J., & Zhao, H. Y. (2023) · Computers in Biology and Medicine · doi:10.1016/j.compbiomed.2023.106650 · Cited by 11

GMFAD: Towards Generalized Visual Recognition via Multilayer Feature Alignment and Disentanglement

Li, H., Wang, S., Wan, R., & Kot, A. C. (2020) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2020.3020554 · Cited by 12

Agnostic Domain Generalization.Preprint

Carlucci, F. M., Russo, P., Tommasi, T., & Barbara Caputo, B. (2018) · arXiv (Cornell University) · Cited by 11

Cross-Dataset Adaptation for Visual Question AnsweringPreprint

Chao, W., Hu, H., & Sha, F. (2018) · arXiv (Cornell University) · doi:10.48550/arxiv.1806.03726 · Cited by 11

Curriculum based Dropout Discriminator for Domain AdaptationPreprint

Kurmi, V. K., Bajaj, V., Subramanian, V. K., & Namboodiri, V. P. (2019) · arXiv (Cornell University) · doi:10.48550/arxiv.1907.10628 · Cited by 11

Mutual Learning Network for Multi-Source Domain AdaptationPreprint

Li, Z., Zhen, Z., Guo, Y., Shen, H., & Ye, J. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2003.12944 · Cited by 19

Confounder Identification-free Causal Visual Feature LearningPreprint

Li, X., Zhang, Z., Wei, G., Lan, C., Zeng, W., Jin, X., & Chen, Z. (2021) · arXiv (Cornell University) · doi:10.48550/arxiv.2111.13420 · Cited by 20

A weighted multi‐source domain adaptation approach for surface defect detection

Hu, B., & Wang, J. (2022) · IET Image Processing · doi:10.1049/ipr2.12484 · Cited by 11

Domain Adaptation: A Survey

Ajith, A., & Gopakumar, G. (2023) · Lecture notes in networks and systems · doi:10.1007/978-981-19-7867-8_47 · Cited by 11

Adaptation via Proxy: Building Instance-Aware Proxy for Unsupervised Domain Adaptive 3D Object Detection

Li, Z., Yao, Y., Quan, Z., Qi, L., Feng, Z., & Yang, W. (2023) · IEEE Transactions on Intelligent Vehicles · doi:10.1109/tiv.2023.3343878 · Cited by 10

Integration of Multikinds Imputation With Covariance Adaptation Based on Evidence Theory

Huang, L., Fan, J., & Liew, A. W. (2024) · IEEE Transactions on Neural Networks and Learning Systems · doi:10.1109/tnnls.2024.3412371 · Cited by 10

Sparse coding-based transfer learning for energy disaggregation

Chouchene, S., Amayri, M., & Bouguila, N. (2024) · Energy and Buildings · doi:10.1016/j.enbuild.2024.114498 · Cited by 10

AD-Aligning: Emulating Human-Like Generalization for Cognitive Domain Adaptation in Deep Learning

Li, Z., Wan, B., Mu, C., Zhao, R., Qiu, S., & Yan, C. (2024) · International Conference on Electronic Communication and Artificial Intelligence (ICECAI) · doi:10.1109/icecai62591.2024.10675013 · Cited by 10

Enhanced cross-domain lithology classification in imbalanced datasets using an unsupervised domain Adversarial Network

Xie, Y., Jin, L., Zhu, C., Luo, W., & Wang, Q. (2024) · Engineering Applications of Artificial Intelligence · doi:10.1016/j.engappai.2024.109668 · Cited by 10

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

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A simple approach for unsupervised domain adaptation

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Simple Domain Adaptation with Class Prediction Uncertainty Alignment.Preprint

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