D-Index & Metrics Best Publications

D-Index & Metrics

Discipline name D-index D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines. Citations Publications World Ranking National Ranking
Computer Science D-index 35 Citations 5,636 98 World Ranking 5857 National Ranking 165

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Machine learning
  • Pattern recognition

Mehrtash Harandi mainly investigates Artificial intelligence, Pattern recognition, Riemannian manifold, Riemannian geometry and Statistical manifold. His Artificial intelligence course of study focuses on Manifold and Embedding. Mehrtash Harandi has researched Pattern recognition in several fields, including Subspace topology and Linear subspace.

As a member of one scientific family, Mehrtash Harandi mostly works in the field of Riemannian manifold, focusing on Kernel and, on occasion, Algorithm, Positive-definite matrix and Matrix. Mehrtash Harandi usually deals with Riemannian geometry and limits it to topics linked to Dimensionality reduction and Geometry and Discriminative model. His Feature extraction research is multidisciplinary, incorporating perspectives in Unsupervised learning, Invariant, Feature vector and Maximum mean discrepancy.

His most cited work include:

  • Going deeper into action recognition (328 citations)
  • Unsupervised Domain Adaptation by Domain Invariant Projection (308 citations)
  • Unsupervised Domain Adaptation by Domain Invariant Projection (308 citations)

What are the main themes of his work throughout his whole career to date?

Mehrtash Harandi mainly investigates Artificial intelligence, Pattern recognition, Manifold, Embedding and Facial recognition system. His Artificial intelligence research incorporates themes from Machine learning, Linear subspace and Computer vision. Mehrtash Harandi works in the field of Pattern recognition, namely Feature extraction.

His Manifold study combines topics from a wide range of disciplines, such as Positive-definite matrix, Matrix, Riemannian manifold, Grassmannian and Riemannian geometry. Mehrtash Harandi studied Riemannian manifold and Projection that intersect with Orthonormal basis. His Embedding study combines topics in areas such as Tangent space, Kullback–Leibler divergence, Hilbert space and Euclidean geometry.

He most often published in these fields:

  • Artificial intelligence (94.04%)
  • Pattern recognition (64.24%)
  • Manifold (27.81%)

What were the highlights of his more recent work (between 2018-2021)?

  • Artificial intelligence (94.04%)
  • Discriminative model (12.58%)
  • Machine learning (23.18%)

In recent papers he was focusing on the following fields of study:

His scientific interests lie mostly in Artificial intelligence, Discriminative model, Machine learning, Pattern recognition and Matrix. His Artificial intelligence research is multidisciplinary, incorporating elements of Margin and Manifold. The various areas that Mehrtash Harandi examines in his Discriminative model study include Subspace topology and Cognitive neuroscience of visual object recognition.

His studies in Machine learning integrate themes in fields like Optical flow and Image. His Pattern recognition study frequently involves adjacent topics like Representation. The Matrix study combines topics in areas such as Measure and Cluster analysis.

Between 2018 and 2021, his most popular works were:

  • Adaptive Subspaces for Few-Shot Learning (42 citations)
  • Bilinear Attention Networks for Person Retrieval (40 citations)
  • Toward Efficient Action Recognition: Principal Backpropagation for Training Two-Stream Networks (19 citations)

In his most recent research, the most cited papers focused on:

  • Artificial intelligence
  • Machine learning
  • Statistics

Mehrtash Harandi focuses on Artificial intelligence, Pooling, Machine learning, Feature extraction and Manifold. Mehrtash Harandi applies his multidisciplinary studies on Artificial intelligence and Block in his research. His Manifold research is multidisciplinary, relying on both Facial recognition system, Kernel, Transformation, Kernel and Pattern recognition.

His study explores the link between Stochastic gradient descent and topics such as Perspective that cross with problems in Contextual image classification and Riemannian geometry. His Subspace topology research focuses on Robustness and how it connects with Cognitive neuroscience of visual object recognition. His studies deal with areas such as Positive-definite matrix, Matrix, Riemannian manifold, Measure and Similarity as well as Discriminative model.

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Best Publications

Going deeper into action recognition

Samitha Herath;Mehrtash Harandi;Fatih Porikli.
Image and Vision Computing (2017)

491 Citations

Unsupervised Domain Adaptation by Domain Invariant Projection

Mahsa Baktashmotlagh;Mahsa Baktashmotlagh;Mehrtash T. Harandi;Mehrtash T. Harandi;Brian C. Lovell;Mathieu Salzmann;Mathieu Salzmann.
international conference on computer vision (2013)

370 Citations

Graph embedding discriminant analysis on Grassmannian manifolds for improved image set matching

Mehrtash T. Harandi;Conrad Sanderson;Sareh Shirazi;Brian C. Lovell.
computer vision and pattern recognition (2011)

315 Citations

Kernel Methods on the Riemannian Manifold of Symmetric Positive Definite Matrices

Sadeep Jayasumana;Richard Hartley;Mathieu Salzmann;Hongdong Li.
computer vision and pattern recognition (2013)

286 Citations

From Manifold to Manifold: Geometry-Aware Dimensionality Reduction for SPD Matrices

Mehrtash Tafazzoli Harandi;Mehrtash Tafazzoli Harandi;Mathieu Salzmann;Mathieu Salzmann;Richard I. Hartley;Richard I. Hartley.
european conference on computer vision (2014)

213 Citations

Sparse coding and dictionary learning for symmetric positive definite matrices: a kernel approach

Mehrtash T. Harandi;Conrad Sanderson;Richard Hartley;Brian C. Lovell.
european conference on computer vision (2012)

203 Citations

Spatio-temporal covariance descriptors for action and gesture recognition

A. Sanin;C. Sanderson;M. T. Harandi;B. C. Lovell.
workshop on applications of computer vision (2013)

190 Citations

Kernel Methods on Riemannian Manifolds with Gaussian RBF Kernels

Sadeep Jayasumana;Richard Hartley;Mathieu Salzmann;Hongdong Li.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2015)

162 Citations

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

Mehrtash Harandi;Mathieu Salzmann;Richard Hartley.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2018)

131 Citations

Kernel analysis over Riemannian manifolds for visual recognition of actions, pedestrians and textures

Mehrtash T. Harandi;Conrad Sanderson;Arnold Wiliem;Brian C. Lovell.
workshop on applications of computer vision (2012)

114 Citations

Best Scientists Citing Mehrtash Harandi

Junbin Gao

Junbin Gao

University of Sydney

Publications: 47

Xilin Chen

Xilin Chen

Institute Of Computing Technology

Publications: 35

Shiguang Shan

Shiguang Shan

Chinese Academy of Sciences

Publications: 34

Ruiping Wang

Ruiping Wang

Chinese Academy of Sciences

Publications: 30

Brian C. Lovell

Brian C. Lovell

University of Queensland

Publications: 29

Conrad Sanderson

Conrad Sanderson

Commonwealth Scientific and Industrial Research Organisation

Publications: 20

Mohamed Daoudi

Mohamed Daoudi

IMT Lille Douai

Publications: 20

Rama Chellappa

Rama Chellappa

Johns Hopkins University

Publications: 20

Vittorio Murino

Vittorio Murino

Italian Institute of Technology

Publications: 19

Fatih Porikli

Fatih Porikli

Australian National University

Publications: 18

Dong Xu

Dong Xu

University of Sydney

Publications: 17

Luc Van Gool

Luc Van Gool

ETH Zurich

Publications: 16

Wanqing Li

Wanqing Li

University of Wollongong

Publications: 16

Wangmeng Zuo

Wangmeng Zuo

Harbin Institute of Technology

Publications: 16

Wen Li

Wen Li

Nanyang Technological University

Publications: 15

Profile was last updated on December 6th, 2021.
Research.com Ranking is based on data retrieved from the Microsoft Academic Graph (MAG).
The ranking d-index is inferred from publications deemed to belong to the considered discipline.

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