World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
41
Citations
7160
World Ranking
8839
National Ranking
350

Overview

Eric Granger is affiliated with the École de Technologie Supérieure in Canada and is active in the field of Computer Science, with a focus on Computer Vision and Pattern Recognition. The scientist's work spans several subfields including Artificial Intelligence, Experimental and Cognitive Psychology, Signal Processing, and Radiology, Nuclear Medicine and Imaging.

Their key research topics include:

  • Advanced Neural Network Applications
  • Video Surveillance and Tracking Methods
  • Domain Adaptation and Few-Shot Learning
  • Emotion and Mood Recognition
  • Advanced Image and Video Retrieval Techniques
  • Face Recognition and Analysis
  • Human Pose and Action Recognition

Frequent coauthors in Eric Granger's research include:

  • Marco Pedersoli
  • Soufiane Belharbi
  • Ismail Ben Ayed
  • Pourya Shamsolmoali
  • Madhu Kiran

Eric Granger has published extensively, particularly in venues such as arXiv (Cornell University), Image and Vision Computing, and the IEEE Transactions on Affective Computing. Other publication outlets include the SSRN Electronic Journal and the 2023 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV).

Some recent papers authored or coauthored by Eric Granger are:

  • Boundary loss for highly unbalanced segmentation, 2020, Medical Image Analysis
  • MDN: A Deep Maximization-Differentiation Network for Spatio-Temporal Depression Detection, 2021, IEEE Transactions on Affective Computing
  • A Deep Multiscale Spatiotemporal Network for Assessing Depression From Facial Dynamics, 2020, IEEE Transactions on Affective Computing
  • A Joint Cross-Attention Model for Audio-Visual Fusion in Dimensional Emotion Recognition, 2022, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)
  • Deep Interpretable Classification and Weakly-Supervised Segmentation of Histology Images via Max-Min Uncertainty, 2021, IEEE Transactions on Medical Imaging

Additionally, Eric Granger has contributed to book publications with Springer Science+Business Media, including works titled Pattern Recognition and Artificial Intelligence published in 2022.

Best Publications

  • Multiple instance learning: A survey of problem characteristics and applications

    Marc-André Carbonneau;Veronika Cheplygina;Veronika Cheplygina;Eric Granger;Ghyslain Gagnon

  • Boundary loss for highly unbalanced segmentation.

    Hoel Kervadec;Jihene Bouchtiba;Christian Desrosiers;Eric Granger

  • Constrained-CNN losses for weakly supervised segmentation.

    Hoel Kervadec;Jose Dolz;Meng Tang;Eric Granger

  • Decoupling Direction and Norm for Efficient Gradient-Based L2 Adversarial Attacks and Defenses

    Jerome Rony;Luiz G. Hafemann;Luiz S. Oliveira;Ismail Ben Ayed

  • A what-and-where fusion neural network for recognition and tracking of multiple radar emitters

    Eric Granger;Mark A. Rubin;Mark A. Rubin;Stephen Grossberg;Pierre Lavoie

  • Pattern Recognition and Artificial Intelligence

    Unknown

  • Iterative Boolean combination of classifiers in the ROC space: An application to anomaly detection with HMMs

    Wael Khreich;Eric Granger;Ali Miri;Robert Sabourin

  • An adaptive classification system for video-based face recognition

    Jean-François Connolly;Eric Granger;Robert Sabourin

  • A survey of techniques for incremental learning of HMM parameters

    Wael Khreich;Eric Granger;Ali Miri;Robert Sabourin

  • Multi-feature extraction and selection in writer-independent off-line signature verification

    Dominique Rivard;Eric Granger;Robert Sabourin

  • Image synthesis with adversarial networks: A comprehensive survey and case studies

    Pourya Shamsolmoali;Pourya Shamsolmoali;Masoumeh Zareapoor;Eric Granger;Huiyu Zhou

  • MDN: A Deep Maximization-Differentiation Network for Spatio-Temporal Depression Detection

    Wheidima Carneirodemelo;Eric G. Granger;Miguel Bordallo Lopez

  • Dynamic selection of generative-discriminative ensembles for off-line signature verification

    Luana Batista;Eric Granger;Robert Sabourin

  • Hybrid writer-independent–writer-dependent offline signature verification system

    George S. Eskander;Robert Sabourin;Eric Granger

  • A Deep Multiscale Spatiotemporal Network for Assessing Depression from Facial Dynamics

    Wheidima Carneiro de Melo;Eric Granger;Abdenour Hadid

  • Unsupervised Domain Adaptation in the Dissimilarity Space for Person Re-identification

    Djebril Mekhazni;Amran Bhuiyan;George S. Eskander Ekladious;Eric Granger

  • A Joint Cross-Attention Model for Audio-Visual Fusion in Dimensional Emotion Recognition

    Unknown

  • A Unifying Mutual Information View of Metric Learning: Cross-Entropy vs. Pairwise Losses

    Malik Boudiaf;Jérôme Rony;Imtiaz Masud Ziko;Eric Granger

  • Pattern Recognition and Artificial Intelligence

    Unknown

  • Combining Global and Local Convolutional 3D Networks for Detecting Depression from Facial Expressions

    Wheidima Carneiro de Melo;Eric Granger;Abdenour Hadid

  • Depression Detection Based on Deep Distribution Learning

    Wheidima Carneiro de Melo;Eric Granger;Abdenour Hadid

  • Partially-supervised learning from facial trajectories for face recognition in video surveillance

    Miguel De-la-Torre;Eric Granger;Paulo V.W. Radtke;Robert Sabourin

  • The Tenth Visual Object Tracking VOT2022 Challenge Results

    Unknown

  • Cascaded Zoom-in Detector for High Resolution Aerial Images

    Unknown

  • Multiregion segmentation of bladder cancer structures in MRI with progressive dilated convolutional networks

    Jose Dolz;Xiaopan Xu;Jérôme Rony;Jing Yuan

  • Adaptive ROC-based ensembles of HMMs applied to anomaly detection

    Wael Khreich;Eric Granger;Ali Miri;Robert Sabourin

  • Bounding boxes for weakly supervised segmentation: Global constraints get close to full supervision

    Hoel Kervadec;Jose Dolz;Shanshan Wang;Eric Granger

  • Intravascular Imaging and Computer Assisted Stenting, and Large-Scale Annotation of Biomedical Data and Expert Label Synthesis

    M.J. Cardoso;T. Arbel;V. Cheplygina;S.-L. Lee

  • Multi-region segmentation of bladder cancer structures in MRI with progressive dilated convolutional networks

    Jose Dolz;Xiaopan Xu;Jerome Rony;Jing Yuan

Frequent Co-Authors

Robert Sabourin
Robert Sabourin École de Technologie Supérieure
Ismail Ben Ayed
Ismail Ben Ayed École de Technologie Supérieure
Fabio Roli
Fabio Roli University of Genoa
Gian Luca Marcialis
Gian Luca Marcialis University of Cagliari
Ali Miri
Ali Miri Toronto Metropolitan University
Christian Desrosiers
Christian Desrosiers École de Technologie Supérieure
Abdenour Hadid
Abdenour Hadid University of Oulu
Stephen Grossberg
Stephen Grossberg Boston University
Giorgio Fumera
Giorgio Fumera University of Cagliari
Luiz S. Oliveira
Luiz S. Oliveira Federal University of Paraná

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