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Mehrtash Harandi

Mehrtash Harandi

D-Index & Metrics

Computer Science

D-Index
47
Citations
8615
World Ranking
6515
National Ranking
204

Overview

Mehrtash Harandi is affiliated with Monash University in Australia and has a research portfolio primarily in computer science. Their work centers on advanced topics within computer vision and artificial intelligence, with a considerable focus on domain adaptation, few-shot learning, and multimodal machine learning applications.

The main fields of study for Mehrtash Harandi cover:

  • Computer Science

Within this broad discipline, their research activity is distributed across several subfields, including:

  • Computer Vision and Pattern Recognition
  • Artificial Intelligence
  • Radiology, Nuclear Medicine and Imaging
  • Computational Mechanics
  • Biomedical Engineering

Harandi's main research topics comprise:

  • Domain Adaptation and Few-Shot Learning
  • Multimodal Machine Learning Applications
  • Advanced Neural Network Applications
  • Human Pose and Action Recognition
  • COVID-19 diagnosis using AI
  • Video Surveillance and Tracking Methods
  • Medical Image Segmentation Techniques

The scientist has published extensively with notable frequent co-authors including:

  • Lars Petersson
  • Gary F. Egan
  • Pengfei Fang
  • Zhaolin Chen
  • Tom Drummond

Publication venues where Mehrtash Harandi's work appears frequently include:

  • arXiv (Cornell University)
  • Proceedings of the AAAI Conference on Artificial Intelligence
  • IEEE Transactions on Pattern Analysis and Machine Intelligence
  • 2021 IEEE/CVF International Conference on Computer Vision (ICCV)
  • Image and Vision Computing

Some recent research papers authored or co-authored by Mehrtash Harandi are:

  • Hierarchical Neural Architecture Search for Deep Stereo Matching, 2020, arXiv (Cornell University)
  • Implicit Motion Handling for Video Camouflaged Object Detection, 2022, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
  • Uncertainty-guided dual-views for semi-supervised volumetric medical image segmentation, 2023, Nature Machine Intelligence
  • Synthesized Feature based Few-Shot Class-Incremental Learning on a Mixture of Subspaces, 2021, 2021 IEEE/CVF International Conference on Computer Vision (ICCV)
  • Domain Adaptation by Joint Distribution Invariant Projections, 2020, IEEE Transactions on Image Processing

Best Publications

  • Going deeper into action recognition

    Samitha Herath;Mehrtash Harandi;Fatih Porikli

  • Unsupervised Domain Adaptation by Domain Invariant Projection

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

  • Adaptive Subspaces for Few-Shot Learning

    Christian Simon;Piotr Koniusz;Richard Nock;Mehrtash Harandi

  • Kernel Methods on the Riemannian Manifold of Symmetric Positive Definite Matrices

    Sadeep Jayasumana;Richard Hartley;Mathieu Salzmann;Hongdong Li

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

    Mehrtash T. Harandi;Conrad Sanderson;Sareh Shirazi;Brian C. Lovell

  • Kernel Methods on Riemannian Manifolds with Gaussian RBF Kernels

    Sadeep Jayasumana;Richard Hartley;Mathieu Salzmann;Hongdong Li

  • 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

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

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

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

    Mehrtash Harandi;Mathieu Salzmann;Richard Hartley

  • Spatio-temporal covariance descriptors for action and gesture recognition

    A. Sanin;C. Sanderson;M. T. Harandi;B. C. Lovell

  • Hierarchical Neural Architecture Search for Deep Stereo Matching

    Xuelian Cheng;Yiran Zhong;Mehrtash Harandi;Yuchao Dai

  • Deep Unsupervised Saliency Detection: A Multiple Noisy Labeling Perspective

    Jing Zhang;Tong Zhang;Yuchao Daf;Mehrtash Harandi

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

    Mehrtash Harandi;Conrad Sanderson;Chunhua Shen;Brian Lovell

  • Bilinear Attention Networks for Person Retrieval

    Pengfei Fang;Jieming Zhou;Soumava Roy;Lars Petersson

  • Semantic-aware Knowledge Distillation for Few-Shot Class-Incremental Learning

    Ali Cheraghian;Shafin Rahman;Pengfei Fang;Soumava Kumar Roy

  • Learning an Invariant Hilbert Space for Domain Adaptation

    Samitha Herath;Samitha Herath;Mehrtash Harandi;Mehrtash Harandi;Fatih Porikli

  • Domain Adaptation on the Statistical Manifold

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

  • Expanding the Family of Grassmannian Kernels: An Embedding Perspective

    Mehrtash Tafazzoli Harandi;Mehrtash Tafazzoli Harandi;Mathieu Salzmann;Mathieu Salzmann;Sadeep Jayasumana;Sadeep Jayasumana;Richard I. Hartley;Richard I. Hartley

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

    Mehrtash T. Harandi;Conrad Sanderson;Arnold Wiliem;Brian C. Lovell

  • Bregman Divergences for Infinite Dimensional Covariance Matrices

    Mehrtash Harandi;Mathieu Salzmann;Fatih Porikli

  • Deep Unsupervised Saliency Detection: A Multiple Noisy Labeling Perspective

    Jing Zhang;Tong Zhang;Yuchao Dai;Mehrtash Harandi

Frequent Co-Authors

Brian C. Lovell
Brian C. Lovell University of Queensland
Conrad Sanderson
Conrad Sanderson Commonwealth Scientific and Industrial Research Organisation
Mathieu Salzmann
Mathieu Salzmann École Polytechnique Fédérale de Lausanne
Richard Hartley
Richard Hartley Australian National University
Fatih Porikli
Fatih Porikli Australian National University
Hongdong Li
Hongdong Li Australian National University
Babak Nadjar Araabi
Babak Nadjar Araabi University of Tehran
Lars Petersson
Lars Petersson Commonwealth Scientific and Industrial Research Organisation
Tong Zhang
Tong Zhang University of Illinois at Urbana-Champaign
Anoop Cherian
Anoop Cherian Mitsubishi Electric (United States)

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