H-Index & Metrics Best Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Computer Science D-index 47 Citations 9,697 151 World Ranking 3310 National Ranking 1728

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Machine learning
  • Statistics

Artificial intelligence, Machine learning, Computer vision, Pattern recognition and Probabilistic logic are his primary areas of study. His Artificial intelligence study frequently draws connections to other fields, such as Active learning. His Machine learning research includes elements of Classifier, Training set and Data mining.

His Image and Frame rate study in the realm of Computer vision connects with subjects such as Graphics, Red-eye effect and Initialization. Ashish Kapoor combines subjects such as Feature detection, Feature and Facial Action Coding System with his study of Pattern recognition. The Probabilistic logic study combines topics in areas such as Categorization, Discriminative model, Kernel and Pyramid.

His most cited work include:

  • AirSim: High-Fidelity Visual and Physical Simulation for Autonomous Vehicles (527 citations)
  • Automatic prediction of frustration (454 citations)
  • Multimodal affect recognition in learning environments (282 citations)

What are the main themes of his work throughout his whole career to date?

Ashish Kapoor spends much of his time researching Artificial intelligence, Machine learning, Computer vision, Pattern recognition and Human–computer interaction. His Artificial intelligence research is multidisciplinary, incorporating perspectives in Active learning and Data mining. His work on Feature as part of general Machine learning research is frequently linked to Gaussian process, thereby connecting diverse disciplines of science.

His Computer vision study incorporates themes from Speech recognition and Facial expression. Ashish Kapoor studies Discriminative model which is a part of Pattern recognition. His study looks at the relationship between Probabilistic logic and topics such as Key, which overlap with Mathematical optimization, Control theory and Control.

He most often published in these fields:

  • Artificial intelligence (56.68%)
  • Machine learning (36.87%)
  • Computer vision (11.52%)

What were the highlights of his more recent work (between 2018-2021)?

  • Artificial intelligence (56.68%)
  • Machine learning (36.87%)
  • Reinforcement learning (5.53%)

In recent papers he was focusing on the following fields of study:

The scientist’s investigation covers issues in Artificial intelligence, Machine learning, Reinforcement learning, Contextual image classification and Artificial neural network. His study in Artificial intelligence is interdisciplinary in nature, drawing from both Computer vision and Pattern recognition. His work on Feature as part of general Machine learning study is frequently linked to Modal, therefore connecting diverse disciplines of science.

Ashish Kapoor interconnects Cognitive psychology, Affect and Curiosity in the investigation of issues within Reinforcement learning. The various areas that Ashish Kapoor examines in his Contextual image classification study include Smoothing, Classifier and Bayesian optimization. Ashish Kapoor works mostly in the field of Artificial neural network, limiting it down to topics relating to Formula SAE and, in certain cases, Human–computer interaction, Formula Student, Deep neural networks and Single camera.

Between 2018 and 2021, his most popular works were:

  • Bias Correction of Learned Generative Models using Likelihood-Free Importance Weighting (40 citations)
  • Do Adversarially Robust ImageNet Models Transfer Better (25 citations)
  • Synthetic Examples Improve Generalization for Rare Classes (17 citations)

In his most recent research, the most cited papers focused on:

  • Artificial intelligence
  • Machine learning
  • Statistics

Ashish Kapoor mainly focuses on Artificial intelligence, Machine learning, Contextual image classification, Deep learning and Transfer of learning. His study ties his expertise on Computer vision together with the subject of Artificial intelligence. His Feature study, which is part of a larger body of work in Machine learning, is frequently linked to Modal, bridging the gap between disciplines.

His Contextual image classification research integrates issues from Classifier, Bayesian optimization and Smoothing. His research brings together the fields of Robustness and Deep learning. His research in Pattern recognition intersects with topics in Generative grammar and Generative model.

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Best Publications

AirSim: High-Fidelity Visual and Physical Simulation for Autonomous Vehicles

Shital Shah;Debadeepta Dey;Chris Lovett;Ashish Kapoor.
field and service robotics (2017)

764 Citations

Automatic prediction of frustration

Ashish Kapoor;Winslow Burleson;Rosalind W. Picard.
International Journal of Human-computer Studies / International Journal of Man-machine Studies (2007)

659 Citations

Multimodal affect recognition in learning environments

Ashish Kapoor;Rosalind W. Picard.
acm multimedia (2005)

411 Citations

Active Learning with Gaussian Processes for Object Categorization

Ashish Kapoor;Kristen Grauman;Raquel Urtasun;Trevor Darrell.
international conference on computer vision (2007)

330 Citations

Image quality assessment

Neel Joshi;Ashish Kapoor;Huixuan Tang.
(2010)

286 Citations

Learning a blind measure of perceptual image quality

Huixuan Tang;Neel Joshi;Ashish Kapoor.
computer vision and pattern recognition (2011)

285 Citations

Farmbeats: an IoT platform for data-driven agriculture

Deepak Vasisht;Zerina Kapetanovic;Jong-ho Won;Xinxin Jin.
networked systems design and implementation (2017)

271 Citations

AffectAura: an intelligent system for emotional memory

Daniel McDuff;Amy Karlson;Ashish Kapoor;Asta Roseway.
human factors in computing systems (2012)

234 Citations

Image tagging based upon cross domain context

Simon John Baker;Ashish Kapoor;Gang Hua;Dahua Lin.
(2011)

221 Citations

EnsembleMatrix: interactive visualization to support machine learning with multiple classifiers

Justin Talbot;Bongshin Lee;Ashish Kapoor;Desney S. Tan.
human factors in computing systems (2009)

217 Citations

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Best Scientists Citing Ashish Kapoor

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Alan C. Bovik

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Sidney K. D'Mello

Sidney K. D'Mello

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Kristen Grauman

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Qiang Ji

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Rensselaer Polytechnic Institute

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Mary Czerwinski

Mary Czerwinski

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Jerome R. Bellegarda

Jerome R. Bellegarda

Apple (United States)

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Dacheng Tao

Dacheng Tao

University of Sydney

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Trevor Darrell

Trevor Darrell

University of California, Berkeley

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Margaret Burnett

Margaret Burnett

Oregon State University

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Eric Horvitz

Eric Horvitz

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Louis-Philippe Morency

Louis-Philippe Morency

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Zhe Lin

Zhe Lin

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Ryan S. Baker

Ryan S. Baker

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