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Mahsa Baktashmotlagh
Mahsa Baktashmotlagh
Verified email at uq.edu.au
Title
Cited by
Cited by
Year
Unsupervised domain adaptation by domain invariant projection
M Baktashmotlagh, MT Harandi, BC Lovell, M Salzmann
Proceedings of the IEEE international conference on computer vision, 769-776, 2013
5302013
Implicit surface representations as layers in neural networks
M Michalkiewicz, JK Pontes, D Jack, M Baktashmotlagh, A Eriksson
Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2019
2472019
Learning to diversify for single domain generalization
Z Wang, Y Luo, R Qiu, Z Huang, M Baktashmotlagh
Proceedings of the IEEE/CVF International Conference on Computer Vision, 834-843, 2021
1962021
Domain adaptation on the statistical manifold
M Baktashmotlagh, MT Harandi, BC Lovell, M Salzmann
Proceedings of the IEEE conference on computer vision and pattern …, 2014
1422014
Correlation-aware adversarial domain adaptation and generalization
MM Rahman, C Fookes, M Baktashmotlagh, S Sridharan
Pattern Recognition 100, 107124, 2020
1282020
Deep level sets: Implicit surface representations for 3d shape inference
M Michalkiewicz, JK Pontes, D Jack, M Baktashmotlagh, A Eriksson
arXiv preprint arXiv:1901.06802, 2019
1222019
Distribution-matching embedding for visual domain adaptation
M Baktashmotlagh, M Har, M Salzmann
Journal of Machine Learning Research 17 (108), 1-30, 2016
1162016
Progressive Graph Learning for Open-Set Domain Adaptation
Y Luo, Z Wang, Z Huang, M Baktashmotlagh
37th International Conference on Machine Learning, 2020
1002020
Multi-component image translation for deep domain generalization
MM Rahman, C Fookes, M Baktashmotlagh, S Sridharan
2019 IEEE Winter Conference on Applications of Computer Vision (WACV), 579-588, 2019
692019
Visualizing student opinion through text analysis
S Cunningham-Nelson, M Baktashmotlagh, W Boles
IEEE Transactions on Education 62 (4), 305-311, 2019
682019
Learning factorized representations for open-set domain adaptation
M Baktashmotlagh, M Faraki, T Drummond, M Salzmann
ICLR, 2019
632019
Beyond gauss: Image-set matching on the riemannian manifold of pdfs
M Harandi, M Salzmann, M Baktashmotlagh
Proceedings of the IEEE International Conference on Computer Vision, 4112-4120, 2015
632015
On minimum discrepancy estimation for deep domain adaptation
MM Rahman, C Fookes, M Baktashmotlagh, S Sridharan
Domain Adaptation for Visual Understanding, 81-94, 2020
602020
Robust domain generalisation by enforcing distribution invariance
S Erfani, M Baktashmotlagh, M Moshtaghi, X Nguyen, C Leckie, J Bailey, ...
Proceedings of the Twenty-Fifth International Joint Conference on Artificial …, 2016
542016
R1SVM: a Randomised Nonlinear Approach to Large-Scale Anomaly Detection
S Erfani, M Baktashmotlagh, S Rajasegarar, S Karunasekera, C Leckie
Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015
462015
Discriminative non-linear stationary subspace analysis for video classification
M Baktashmotlagh, M Harandi, BC Lovell, M Salzmann
IEEE transactions on pattern analysis and machine intelligence 36 (12), 2353 …, 2014
452014
Adversarial bipartite graph learning for video domain adaptation
Y Luo, Z Huang, Z Wang, Z Zhang, M Baktashmotlagh
Proceedings of the 28th ACM International Conference on Multimedia, 19-27, 2020
412020
Robust re-identification of manta rays from natural markings by learning pose invariant embeddings
O Moskvyak, F Maire, F Dayoub, AO Armstrong, M Baktashmotlagh
2021 Digital Image Computing: Techniques and Applications (DICTA), 1-8, 2021
402021
Closing the gap of simulation to reality in electromagnetic imaging of brain strokes via deep neural networks
A Al-Saffar, A Bialkowski, M Baktashmotlagh, A Trakic, L Guo, A Abbosh
IEEE Transactions on Computational Imaging 7, 13-21, 2020
362020
Prototype-matching graph network for heterogeneous domain adaptation
Z Wang, Y Luo, Z Huang, M Baktashmotlagh
Proceedings of the 28th ACM International Conference on Multimedia, 2104-2112, 2020
272020
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