World's Best Scientists 2026 revealed!
Eric L. Schwartz

Eric L. Schwartz

D-Index & Metrics

Computer Science

D-Index
42
Citations
9048
World Ranking
8274
National Ranking
3547

Overview

Eric L. Schwartz was affiliated with Boston University in the United States and contributed to the field of Computer Science, particularly focusing on subfields such as Computer Vision and Pattern Recognition, Artificial Intelligence, Radiology, Nuclear Medicine and Imaging, Media Technology, and Computer Graphics and Computer-Aided Design.

Their research spanned various topics, prominently featuring

  • Domain Adaptation and Few-Shot Learning
  • Multimodal Machine Learning Applications
  • Advanced Neural Network Applications
  • Advanced Image and Video Retrieval Techniques
  • Anomaly Detection Techniques and Applications
  • Image and Signal Denoising Methods
  • Adversarial Robustness in Machine Learning

The scientist published extensively in multiple venues, notably

  • arXiv (Cornell University)
  • Pattern Recognition Letters
  • Computer Vision and Image Understanding
  • 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
  • Mathematics

Among their recent papers were:

  • "Baby steps towards few-shot learning with multiple semantics", 2022, Pattern Recognition Letters
  • "MAEDAY: MAE for few- and zero-shot AnomalY-Detection", 2024, Computer Vision and Image Understanding

Other works connected to their collaboration network included papers presented at notable conferences and journals such as the Proceedings of the AAAI Conference on Artificial Intelligence, with titles like "StarNet: towards Weakly Supervised Few-Shot Object Detection" (2021) and others addressing neural network quantization and domain generalization.

Frequent co-authors in their collaborative research projects included Raja Giryes, Leonid Karlinsky, Rogério Feris, Assaf Arbelle, and Sivan Doveh. These collaborations contributed to a substantial number of joint publications, indicating a consistent research partnership with experts in similar fields and topics.

Eric L. Schwartz's body of work primarily engaged with machine learning techniques applied to computer vision challenges and anomaly detection, blending theoretical and applied approaches in various contexts and domains.

Best Publications

  • The isomap algorithm and topological stability.

    Mukund Balasubramanian;Eric L. Schwartz

  • Spatial mapping in the primate sensory projection: Analytic structure and relevance to perception

    E. L. Schwartz

  • Computational anatomy and functional architecture of striate cortex: A spatial mapping approach to perceptual coding

    Eric L. Schwartz

  • Computational neuroscience

    Eric L. Schwartz

  • Isoperimetric graph partitioning for image segmentation

    L. Grady;E.L. Schwartz

  • Shape recognition and inferior temporal neurons.

    E L Schwartz;R Desimone;T D Albright;C G Gross

  • Accurate prediction of V1 location from cortical folds in a surface coordinate system

    Oliver P. Hinds;Niranjini Rajendran;Jonathan R. Polimeni;Jean C. Augustinack

  • A numerical solution to the generalized mapmaker's problem: flattening nonconvex polyhedral surfaces

    E.L. Schwartz;A. Shaw;E. Wolfson

  • Design considerations for a space-variant visual sensor with complex-logarithmic geometry

    A.S. Rojer;E.L. Schwartz

  • Cepstral Filtering on a Columnar Image Architecture: A Fast Algorithm for Binocular Stereo Segmentation

    Y. Yeshurun;E.L. Schwartz

  • The Neurophysiology of Information Processing and Cognition

    E R John;E L Schwartz

  • Space Variant Image Processing

    Richard S. Wallace;Ping-Wen Ong;Benjamin B. Bederson;Eric L. Schwartz

  • Improving sterological estimates for the volume of structures identified in three-dimensional arrays of spatial data

    Patrick E. Barta;Lara Dhingra;Richard Royall;Eric Schwartz

  • Space-variant active vision: definition, overview and examples

    Eric L. Schwartz;Douglas N. Greve;Giorgio Bonmassar

  • Cat and monkey cortical columnar patterns modeled by bandpass-filtered 2D white noise

    A. S. Rojer;E. L. Schwartz

  • Locating the functional and anatomical boundaries of human primary visual cortex.

    Oliver Hinds;Jonathan R. Polimeni;Niranjini Rajendran;Mukund Balasubramanian

  • Computing with the leaky integrate-and-fire neuron: logarithmic computation and multiplication

    Doron Tal;Eric L. Schwartz

  • Inferior Temporal Cortex and Pattern Recognition

    C. G. Gross;R. Desimone;T. D. Albright;E. L. Schwartz

  • A quantitative model of the functional architecture of human striate cortex with application to visual illusion and cortical texture analysis

    Eric L. Schwartz

  • Multi-area visuotopic map complexes in macaque striate and extra-striate cortex

    Jonathan R. Polimeni;Mukund Balasubramanian;Eric L. Schwartz

  • Adaptive nonlocal filtering: a fast alternative to anisotropic diffusion for image enhancement

    B. Fischl;E.L. Schwartz

Frequent Co-Authors

Bruce Fischl
Bruce Fischl Harvard University
Benjamin B. Bederson
Benjamin B. Bederson University of Maryland, College Park
Giorgio Bonmassar
Giorgio Bonmassar Massachusetts General Hospital
Lawrence L. Wald
Lawrence L. Wald Harvard University
Jean C. Augustinack
Jean C. Augustinack Harvard University
Douglas N. Greve
Douglas N. Greve Harvard University
Thomas D. Albright
Thomas D. Albright Salk Institute for Biological Studies
Charles G. Gross
Charles G. Gross Princeton University

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