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Computer Science

D-Index
71
Citations
53060
World Ranking
1720
National Ranking
874

Overview

Laurent Itti is affiliated with the University of Southern California in the United States and specializes in the field of computer science, focusing on subfields such as computer vision and pattern recognition, artificial intelligence, cognitive neuroscience, electrical and electronic engineering, and aerospace engineering.

Their research spans a variety of main topics including:

  • Domain Adaptation and Few-Shot Learning
  • Multimodal Machine Learning Applications
  • Advanced Neural Network Applications
  • Human Pose and Action Recognition
  • Advanced Image and Video Retrieval Techniques
  • Adversarial Robustness in Machine Learning
  • Reinforcement Learning in Robotics

Laurent Itti has contributed to multiple scientific publications, with a considerable number appearing in arXiv (Cornell University). Other notable publication venues include the 2023 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), Scientific Journal of Artificial Intelligence and Blockchain Technologies, Nature Biomedical Engineering, and Nature Machine Intelligence.

The following are some of their recent papers along with publication years and venues:

  • Rapid adaptation of brain-computer interfaces to new neuronal ensembles or participants via generative modelling, 2021, Nature Biomedical Engineering
  • A collective AI via lifelong learning and sharing at the edge, 2024, Nature Machine Intelligence
  • Eye tracking identifies biomarkers in α-synucleinopathies versus progressive supranuclear palsy, 2022, Journal of Neurology
  • An Object-Based Bayesian Framework for Top-Down Visual Attention, 2021, Proceedings of the AAAI Conference on Artificial Intelligence
  • Beneficial Perturbation Network for Designing General Adaptive Artificial Intelligence Systems, 2021, IEEE Transactions on Neural Networks and Learning Systems

Frequent co-authors working alongside Laurent Itti include:

  • Yunhao Ge
  • Sumedh Sontakke
  • Shixian Wen
  • Kiran Lekkala
  • Amanda Rios

Best Publications

  • A model of saliency-based visual attention for rapid scene analysis

    L. Itti;C. Koch;E. Niebur

  • Computational modelling of visual attention.

    Laurent Itti;Christof Koch

  • A saliency-based search mechanism for overt and covert shifts of visual attention.

    Laurent Itti;Christof Koch

  • State-of-the-Art in Visual Attention Modeling

    A. Borji;L. Itti

  • Bayesian surprise attracts human attention.

    Laurent Itti;Pierre Baldi

  • Automatic foveation for video compression using a neurobiological model of visual attention

    L. Itti

  • Modeling the influence of task on attention

    Vidhya Navalpakkam;Laurent Itti

  • Components of bottom-up gaze allocation in natural images

    Robert J. Peters;Asha Iyer;Laurent Itti;Christof Koch

  • Quantitative Analysis of Human-Model Agreement in Visual Saliency Modeling: A Comparative Study

    Ali Borji;D. N. Sihite;L. Itti

  • Rapid Biologically-Inspired Scene Classification Using Features Shared with Visual Attention

    C. Siagian;L. Itti

  • Born Again Neural Networks

    Tommaso Furlanello;Zachary Chase Lipton;Michael Tschannen;Laurent Itti

  • Feature combination strategies for saliency-based visual attention systems

    Laurent Itti;Christof Koch

  • Attention activates winner-take-all competition among visual filters

    D. K. Lee;Laurent Itti;Christof Koch;Jochen Braun

  • Salient object detection: a benchmark

    Ali Borji;Dicky N. Sihite;Laurent Itti

  • An Integrated Model of Top-Down and Bottom-Up Attention for Optimizing Detection Speed

    V. Navalpakkam;L. Itti

  • A principled approach to detecting surprising events in video

    L. Itti;P. Baldi

  • Quantifying center bias of observers in free viewing of dynamic natural scenes.

    Po-He Tseng;Ran Carmi;Ian G. M. Cameron;Douglas P. Munoz

  • Exploiting local and global patch rarities for saliency detection

    Ali Borji;Laurent Itti

  • Quantifying the contribution of low-level saliency to human eye movements in dynamic scenes.

    Laurent Itti

  • Neurobiology of attention

    Laurent Itti;Geraint Rees;John K. Tsotsos

Frequent Co-Authors

Ali Borji
Ali Borji Quintic AI
Douglas P. Munoz
Douglas P. Munoz Queen's University
Christof Koch
Christof Koch Allen Institute for Brain Science
Pierre Baldi
Pierre Baldi University of California, Irvine
Tadashi Isa
Tadashi Isa Kyoto University
Michael A. Arbib
Michael A. Arbib University of Southern California
James D. Weiland
James D. Weiland University of Michigan–Ann Arbor
James N. Reynolds
James N. Reynolds Queen's University
Kyle Brauer Boone
Kyle Brauer Boone Alliant International University
Zachary C. Lipton
Zachary C. Lipton Carnegie Mellon University

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