A unified framework for visual domain adaptation with covariance matching

[1]  R. Sanodiya,et al.  A Novel Angular-Based Unsupervised Domain Adaptation Framework for Image Classification , 2024, IEEE Transactions on Artificial Intelligence.

[2]  A. Savakis,et al.  Continual Unsupervised Domain Adaptation in Data-Constrained Environments , 2024, IEEE Transactions on Artificial Intelligence.

[3]  B. R. Jose,et al.  Visual Domain Adaptation through Locality Information , 2023, Eng. Appl. Artif. Intell..

[4]  Jimson Mathew,et al.  Unsupervised sub-domain adaptation using optimal transport , 2023, J. Vis. Commun. Image Represent..

[5]  P. Honeine,et al.  Unsupervised domain adaptation for regression using dictionary learning , 2023, Knowl. Based Syst..

[6]  Deyun Zhou,et al.  Unsupervised domain adaptation via progressive positioning of target-class prototypes , 2023, Knowl. Based Syst..

[7]  J. Dezert,et al.  Cross-Domain Pattern Classification With Distribution Adaptation Based on Evidence Theory , 2021, IEEE Transactions on Cybernetics.

[8]  Mourad El Hamri,et al.  Hierarchical optimal transport for unsupervised domain adaptation , 2021, Machine Learning.

[9]  M. Tiwari,et al.  Machine learning in manufacturing and industry 4.0 applications , 2021, Int. J. Prod. Res..

[10]  Jiajun Bu,et al.  Uncertainty-Guided Mixup for Semi-Supervised Domain Adaptation without Source Data , 2021, Knowl. Based Syst..

[11]  Rakesh Kumar Sanodiya,et al.  Discriminative information preservation: A general framework for unsupervised visual Domain Adaptation , 2021, Knowl. Based Syst..

[12]  Kannan Achan,et al.  Theoretical Understandings of Product Embedding for E-commerce Machine Learning , 2021, WSDM.

[13]  Liran Yang,et al.  Discriminative and informative joint distribution adaptation for unsupervised domain adaptation , 2020, Knowl. Based Syst..

[14]  David Zhang,et al.  Guide Subspace Learning for Unsupervised Domain Adaptation , 2020, IEEE Transactions on Neural Networks and Learning Systems.

[15]  Jafar Tahmoresnezhad,et al.  Joint distinct subspace learning and unsupervised transfer classification for visual domain adaptation , 2020, Signal, Image and Video Processing.

[16]  Haibo He,et al.  Discriminant Geometrical and Statistical Alignment With Density Peaks for Domain Adaptation , 2020, IEEE Transactions on Cybernetics.

[17]  Lei Tian,et al.  Domain Adaptation by Class Centroid Matching and Local Manifold Self-Learning , 2020, IEEE Transactions on Image Processing.

[18]  Dapeng Wu,et al.  Discriminative Transfer Feature and Label Consistency for Cross-Domain Image Classification , 2020, IEEE Transactions on Neural Networks and Learning Systems.

[19]  Jimson Mathew,et al.  A Kernelized Unified Framework for Domain Adaptation , 2019, IEEE Access.

[20]  Dongrui Wu,et al.  Discriminative Joint Probability Maximum Mean Discrepancy (DJP-MMD) for Domain Adaptation , 2019, 2020 International Joint Conference on Neural Networks (IJCNN).

[21]  Tieniu Tan,et al.  Exploring uncertainty in pseudo-label guided unsupervised domain adaptation , 2019, Pattern Recognit..

[22]  Jimson Mathew,et al.  A novel unsupervised Globality-Locality Preserving Projections in transfer learning , 2019, Image Vis. Comput..

[23]  Hao Wang,et al.  Semi-supervised representation learning via dual autoencoders for domain adaptation , 2019, Knowl. Based Syst..

[24]  Jimson Mathew,et al.  A framework for semi-supervised metric transfer learning on manifolds , 2019, Knowl. Based Syst..

[25]  Tieniu Tan,et al.  Distant Supervised Centroid Shift: A Simple and Efficient Approach to Visual Domain Adaptation , 2019, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

[26]  Zhenan Sun,et al.  Aggregating Randomized Clustering-Promoting Invariant Projections for Domain Adaptation , 2019, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[27]  Trevor Darrell,et al.  Semi-Supervised Domain Adaptation via Minimax Entropy , 2019, 2019 IEEE/CVF International Conference on Computer Vision (ICCV).

[28]  Diane J. Cook,et al.  A Survey of Unsupervised Deep Domain Adaptation , 2018, ACM Trans. Intell. Syst. Technol..

[29]  Philip S. Yu,et al.  Visual Domain Adaptation with Manifold Embedded Distribution Alignment , 2018, ACM Multimedia.

[30]  Dong Xu,et al.  Collaborative and Adversarial Network for Unsupervised Domain Adaptation , 2018, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.

[31]  Cheng Wu,et al.  Domain Invariant and Class Discriminative Feature Learning for Visual Domain Adaptation , 2018, IEEE Transactions on Image Processing.

[32]  M. A. Jabbar,et al.  Machine Learning in Healthcare: A Review , 2018, 2018 Second International Conference on Electronics, Communication and Aerospace Technology (ICECA).

[33]  Zhiguo Cao,et al.  An Embarrassingly Simple Approach to Visual Domain Adaptation , 2018, IEEE Transactions on Image Processing.

[34]  Tatsuya Harada,et al.  Maximum Classifier Discrepancy for Unsupervised Domain Adaptation , 2017, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.

[35]  Donald A. Adjeroh,et al.  Unified Deep Supervised Domain Adaptation and Generalization , 2017, 2017 IEEE International Conference on Computer Vision (ICCV).

[36]  Jian Shen,et al.  Wasserstein Distance Guided Representation Learning for Domain Adaptation , 2017, AAAI.

[37]  Sethuraman Panchanathan,et al.  Deep Hashing Network for Unsupervised Domain Adaptation , 2017, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[38]  Hui Xiong,et al.  A Unified Framework for Metric Transfer Learning , 2017, IEEE Transactions on Knowledge and Data Engineering.

[39]  Jing Zhang,et al.  Joint Geometrical and Statistical Alignment for Visual Domain Adaptation , 2017, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[40]  Trevor Darrell,et al.  Adversarial Discriminative Domain Adaptation , 2017, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[41]  Qiang Yang,et al.  Distant Domain Transfer Learning , 2017, AAAI.

[42]  Yiming Yang,et al.  Cross-Domain Kernel Induction for Transfer Learning , 2017, AAAI.

[43]  Kate Saenko,et al.  Correlation Alignment for Unsupervised Domain Adaptation , 2016, Domain Adaptation in Computer Vision Applications.

[44]  Mehrtash Tafazzoli Harandi,et al.  Learning an Invariant Hilbert Space for Domain Adaptation , 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[45]  Kate Saenko,et al.  Deep CORAL: Correlation Alignment for Deep Domain Adaptation , 2016, ECCV Workshops.

[46]  Michael I. Jordan,et al.  Deep Transfer Learning with Joint Adaptation Networks , 2016, ICML.

[47]  Xuelong Li,et al.  Discriminative Transfer Subspace Learning via Low-Rank and Sparse Representation , 2016, IEEE Transactions on Image Processing.

[48]  Mengjie Zhang,et al.  Scatter Component Analysis: A Unified Framework for Domain Adaptation and Domain Generalization , 2015, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[49]  François Laviolette,et al.  Domain-Adversarial Training of Neural Networks , 2015, J. Mach. Learn. Res..

[50]  James Philbin,et al.  FaceNet: A unified embedding for face recognition and clustering , 2015, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[51]  Michael I. Jordan,et al.  Learning Transferable Features with Deep Adaptation Networks , 2015, ICML.

[52]  Victor S. Lempitsky,et al.  Unsupervised Domain Adaptation by Backpropagation , 2014, ICML.

[53]  Philip S. Yu,et al.  Transfer Joint Matching for Unsupervised Domain Adaptation , 2014, 2014 IEEE Conference on Computer Vision and Pattern Recognition.

[54]  Philip S. Yu,et al.  Adaptation Regularization: A General Framework for Transfer Learning , 2014, IEEE Transactions on Knowledge and Data Engineering.

[55]  Philip S. Yu,et al.  Transfer Feature Learning with Joint Distribution Adaptation , 2013, 2013 IEEE International Conference on Computer Vision.

[56]  Tinne Tuytelaars,et al.  Unsupervised Visual Domain Adaptation Using Subspace Alignment , 2013, 2013 IEEE International Conference on Computer Vision.

[57]  Trevor Darrell,et al.  Rich Feature Hierarchies for Accurate Object Detection and Semantic Segmentation , 2013, 2014 IEEE Conference on Computer Vision and Pattern Recognition.

[58]  Trevor Darrell,et al.  DeCAF: A Deep Convolutional Activation Feature for Generic Visual Recognition , 2013, ICML.

[59]  Kristen Grauman,et al.  Connecting the Dots with Landmarks: Discriminatively Learning Domain-Invariant Features for Unsupervised Domain Adaptation , 2013, ICML.

[60]  Geoffrey E. Hinton,et al.  ImageNet classification with deep convolutional neural networks , 2012, Commun. ACM.

[61]  Yuan Shi,et al.  Geodesic flow kernel for unsupervised domain adaptation , 2012, 2012 IEEE Conference on Computer Vision and Pattern Recognition.

[62]  Qiang Yang,et al.  A Survey on Transfer Learning , 2010, IEEE Transactions on Knowledge and Data Engineering.

[63]  Trevor Darrell,et al.  Adapting Visual Category Models to New Domains , 2010, ECCV.

[64]  Ivor W. Tsang,et al.  Domain Adaptation via Transfer Component Analysis , 2009, IEEE Transactions on Neural Networks.

[65]  Qiang Yang,et al.  Transfer Learning via Dimensionality Reduction , 2008, AAAI.

[66]  Bernhard Schölkopf,et al.  A Kernel Method for the Two-Sample-Problem , 2006, NIPS.

[67]  Pietro Perona,et al.  Learning Generative Visual Models from Few Training Examples: An Incremental Bayesian Approach Tested on 101 Object Categories , 2004, 2004 Conference on Computer Vision and Pattern Recognition Workshop.

[68]  Terence Sim,et al.  The CMU Pose, Illumination, and Expression Database , 2003, IEEE Trans. Pattern Anal. Mach. Intell..

[69]  Marti A. Hearst.  Support vector machines , 1998 .

[70]  Jonathan J. Hull,et al.  A Database for Handwritten Text Recognition Research , 1994, IEEE Trans. Pattern Anal. Mach. Intell..

[71]  K. Esbensen,et al.  Principal component analysis , 1987 .

[72]  Rakesh Kumar Sanodiya,et al.  Linear Discriminant Analysis via Pseudo Labels: A Unified Framework for Visual Domain Adaptation , 2020, IEEE Access.

[73]  Yoshua Bengio,et al.  Gradient-based learning applied to document recognition , 1998, Proc. IEEE.

[74]  Peter E. Hart,et al.  Nearest neighbor pattern classification , 1967, IEEE Trans. Inf. Theory.