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Computer Science

D-Index
55
Citations
9543
World Ranking
4393
National Ranking
2049

Research.com Recognitions

  • 2019 - Fellow of John Simon Guggenheim Memorial Foundation

Overview

Miguel P. Eckstein is affiliated with the University of California, Santa Barbara in the United States. The primary research spans the fields of Computer Science and Neuroscience, with notable focus on Cognitive Neuroscience, Computer Vision and Pattern Recognition, Artificial Intelligence, Radiology, Nuclear Medicine and Imaging, and Human-Computer Interaction.

The research topics covered include:

  • Visual Attention and Saliency Detection
  • Visual perception and processing mechanisms
  • Face Recognition and Perception
  • Multimodal Machine Learning Applications
  • Neural dynamics and brain function
  • Natural Language Processing Techniques
  • Topic Modeling

Frequent publication venues for this scientist's work are:

  • Journal of Vision
  • arXiv (Cornell University)
  • Journal of Medical Imaging
  • bioRxiv (Cold Spring Harbor Laboratory)
  • Psychonomic Bulletin & Review

Miguel P. Eckstein's recent papers include:

  • "Diagnosing Vision-and-Language Navigation: What Really Matters" (2022), published in Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
  • "Under-exploration of Three-Dimensional Images Leads to Search Errors for Small Salient Targets" (2021), published in Current Biology
  • "Measurement of the useful field of view for single slices of different imaging modalities and targets" (2020), published in Journal of Medical Imaging
  • "Foveated Model Observers for Visual Search in 3D Medical Images" (2020), published in IEEE Transactions on Medical Imaging
  • "Imagination-Augmented Natural Language Understanding" (2022), published in Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies

Frequent collaborators across multiple projects include:

  • William Yang Wang
  • Craig K. Abbey
  • Shravan Murlidaran
  • Nicole Han
  • Wanrong Zhu

The scientist was awarded the distinction of Fellow of the John Simon Guggenheim Memorial Foundation in 2019.

Best Publications

  • Visual search: a retrospective.

    Miguel P. Eckstein

  • Spatial covert attention increases contrast sensitivity across the CSF: support for signal enhancement☆

    Marisa Carrasco;Cigdem Penpeci-Talgar;Miguel Eckstein

  • A signal detection model predicts the effects of set size on visual search accuracy for feature, conjunction, triple conjunction, and disjunction displays.

    Miguel P. Eckstein;James P. Thomas;John Palmer;Steven S. Shimozaki

  • Looking just below the eyes is optimal across face recognition tasks

    Matthew F. Peterson;Miguel P. Eckstein

  • The Lower Visual Search Efficiency for Conjunctions Is Due to Noise and not Serial Attentional Processing

    Miguel P. Eckstein

  • Attentional Cues in Real Scenes, Saccadic Targeting, and Bayesian Priors

    Miguel P. Eckstein;Barbara A. Drescher;Steven S. Shimozaki

  • Individual Differences in Eye Movements During Face Identification Reflect Observer-Specific Optimal Points of Fixation

    Matthew F. Peterson;Miguel P. Eckstein

  • The footprints of visual attention in the Posner cueing paradigm revealed by classification images

    Miguel P. Eckstein;Steven S. Shimozaki;Craig K. Abbey

  • What do saliency models predict

    Kathryn Koehler;Fei Guo;Sheng Zhang;Miguel P. Eckstein

  • Visual signal detection in structured backgrounds. II. Effects of contrast gain control, background variations, and white noise

    Miguel P. Eckstein;Albert J. Ahumada;Andrew B. Watson

  • Object co-occurrence serves as a contextual cue to guide and facilitate visual search in a natural viewing environment.

    Stephen C. Mack;Miguel P. Eckstein

  • Statistical texture synthesis of mammographic images with super-blob lumpy backgrounds.

    François O. Bochud;Craig K. Abbey;Miguel P. Eckstein

  • Classification image analysis: estimation and statistical inference for two-alternative forced-choice experiments

    Craig K. Abbey;Miguel P. Eckstein

  • The time course of visual information accrual guiding eye movement decisions

    Avi Caspi;Brent R. Beutter;Miguel P. Eckstein

  • Classification images: A tool to analyze visual strategies

    Miguel P. Eckstein;Albert J. Ahumada

  • Signal detection theory applied to three visual search tasks — identification, yes/no detection and localization

    E. Leslie Cameron;Joanna C. Tai;Miguel P. Eckstein;Marisa Carrasco

  • Single-Trial Classification of Event-Related Potentials in Rapid Serial Visual Presentation Tasks Using Supervised Spatial Filtering

    Hubert Cecotti;Miguel P. Eckstein;Barry Giesbrecht

  • Stabilized estimates of Hotelling-observer detection performance in patient-structured noise

    Harrison H. Barrett;Craig K. Abbey;Brandon D. Gallas;Miguel P. Eckstein

  • Automated computer evaluation and optimization of image compression of x-ray coronary angiograms for signal known exactly detection tasks.

    Miguel P. Eckstein;Jay L. Bartroff;Craig K. Abbey;James S. Whiting

  • A Practical Guide to Model Observers for Visual Detection in Synthetic and Natural Noisy Images

    Miguel P. Eckstein;Craig K. Abbey;François O. Bochud

Frequent Co-Authors

Craig K. Abbey
Craig K. Abbey University of California, Santa Barbara
William Yang Wang
William Yang Wang University of California, Santa Barbara
Scott T. Grafton
Scott T. Grafton University of California, Santa Barbara
Marisa Carrasco
Marisa Carrasco New York University
Albert J. Ahumada
Albert J. Ahumada Ames Research Center
Kyle J. Myers
Kyle J. Myers Texas A&M University
Andrew B. Watson
Andrew B. Watson Apple (United States)
Ehsan Samei
Ehsan Samei Duke University
Richard J. Krauzlis
Richard J. Krauzlis National Institutes of Health
Francesco Bullo
Francesco Bullo University of California, Santa Barbara

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