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Dimensionality Reduction on SPD Manifolds: The Emergence of Geometry-Aware Methods
Dimensionality Reduction on SPD Manifolds: The Emergence of Geometry-Aware Methods
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Dimensionality Reduction on SPD Manifolds: The Emergence of Geometry-Aware Methods

Harandi, Mehrtash ; Salzmann, Mathieu ; Hartley, Richard

IEEE transactions on pattern analysis and machine intelligence, 2018-01, Vol.40 (1), p.48-62 [Peer Reviewed Journal]

United States: IEEE

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Unsupervised Domain Adaptation by Domain Invariant Projection
Unsupervised Domain Adaptation by Domain Invariant Projection
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Conference Proceeding 		Add to e-Shelf

Unsupervised Domain Adaptation by Domain Invariant Projection

Baktashmotlagh, Mahsa ; Harandi, Mehrtash T. ; Lovell, Brian C. ; Salzmann, Mathieu

2013 IEEE International Conference on Computer Vision, 2013, p.769-776

IEEE

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3
Attention in Attention Networks for Person Retrieval
Attention in Attention Networks for Person Retrieval
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Attention in Attention Networks for Person Retrieval

Fang, Pengfei ; Zhou, Jieming ; Roy, Soumava Kumar ; Ji, Pan ; Petersson, Lars ; Harandi, Mehrtash

IEEE transactions on pattern analysis and machine intelligence, 2022-09, Vol.44 (9), p.4626-4641 [Peer Reviewed Journal]

United States: IEEE

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4
Learning Log-Determinant Divergences for Positive Definite Matrices
Learning Log-Determinant Divergences for Positive Definite Matrices
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Learning Log-Determinant Divergences for Positive Definite Matrices

Cherian, Anoop ; Stanitsas, Panagiotis ; Wang, Jue ; Harandi, Mehrtash ; Morellas, Vassilios ; Papanikolopoulos, Nikolaos

IEEE transactions on pattern analysis and machine intelligence, 2022-09, Vol.44 (9), p.5088-5102 [Peer Reviewed Journal]

United States: IEEE

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5
Learning Saliency From Single Noisy Labelling: A Robust Model Fitting Perspective
Learning Saliency From Single Noisy Labelling: A Robust Model Fitting Perspective
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Learning Saliency From Single Noisy Labelling: A Robust Model Fitting Perspective

Zhang, Jing ; Dai, Yuchao ; Zhang, Tong ; Harandi, Mehrtash ; Barnes, Nick ; Hartley, Richard

IEEE transactions on pattern analysis and machine intelligence, 2021-08, Vol.43 (8), p.2866-2873 [Peer Reviewed Journal]

United States: IEEE

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6
Sparse Coding on Symmetric Positive Definite Manifolds Using Bregman Divergences
Sparse Coding on Symmetric Positive Definite Manifolds Using Bregman Divergences
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Sparse Coding on Symmetric Positive Definite Manifolds Using Bregman Divergences

Harandi, Mehrtash T. ; Hartley, Richard ; Lovell, Brian ; Sanderson, Conrad

IEEE transaction on neural networks and learning systems, 2016-06, Vol.27 (6), p.1294-1306

United States: IEEE

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7
Dictionary Learning and Sparse Coding on Grassmann Manifolds: An Extrinsic Solution
Dictionary Learning and Sparse Coding on Grassmann Manifolds: An Extrinsic Solution
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Dictionary Learning and Sparse Coding on Grassmann Manifolds: An Extrinsic Solution

Harandi, Mehrtash ; Sanderson, Conrad ; Chunhua Shen ; Lovell, Brian

2013 IEEE International Conference on Computer Vision, 2013, p.3120-3127

IEEE

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8
Large-Scale Metric Learning: A Voyage From Shallow to Deep
Large-Scale Metric Learning: A Voyage From Shallow to Deep
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Large-Scale Metric Learning: A Voyage From Shallow to Deep

Faraki, Masoud ; Harandi, Mehrtash T. ; Porikli, Fatih

IEEE transaction on neural networks and learning systems, 2018-09, Vol.29 (9), p.4339-4346

United States: IEEE

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9
Extrinsic Methods for Coding and Dictionary Learning on Grassmann Manifolds
Extrinsic Methods for Coding and Dictionary Learning on Grassmann Manifolds
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Extrinsic Methods for Coding and Dictionary Learning on Grassmann Manifolds

Harandi, Mehrtash ; Hartley, Richard ; Shen, Chunhua ; Lovell, Brian ; Sanderson, Conrad

International journal of computer vision, 2015-09, Vol.114 (2-3), p.113-136 [Peer Reviewed Journal]

New York: Springer US

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10
No fuss metric learning, a Hilbert space scenario
No fuss metric learning, a Hilbert space scenario
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No fuss metric learning, a Hilbert space scenario

Faraki, Masoud ; T. Harandi, Mehrtash ; Porikli, Fatih

Pattern recognition letters, 2017-10, Vol.98, p.83-89 [Peer Reviewed Journal]

Amsterdam: Elsevier B.V

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