D-Index & Metrics Best Publications

D-Index & Metrics

Discipline name D-index D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines. Citations Publications World Ranking National Ranking
Computer Science D-index 40 Citations 8,726 130 World Ranking 4526 National Ranking 421

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Machine learning
  • Computer vision

His primary areas of study are Artificial intelligence, Pattern recognition, Computer vision, Convolutional neural network and Image texture. His Artificial intelligence study often links to related topics such as Bayesian multivariate linear regression. His work on Feature extraction, Feature vector and Support vector machine as part of general Pattern recognition research is frequently linked to Gaussian process, bridging the gap between disciplines.

His Video tracking, Eye tracking, Object and Tracking study in the realm of Computer vision connects with subjects such as Memory controller. As a member of one scientific family, Antoni B. Chan mostly works in the field of Convolutional neural network, focusing on Pose and, on occasion, Monocular, Deep learning and Structured prediction. His Image texture study integrates concerns from other disciplines, such as Motion estimation and Mixture model.

His most cited work include:

  • Supervised Learning of Semantic Classes for Image Annotation and Retrieval (838 citations)
  • Privacy preserving crowd monitoring: Counting people without people models or tracking (792 citations)
  • Modeling, Clustering, and Segmenting Video with Mixtures of Dynamic Textures (334 citations)

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

Antoni B. Chan mostly deals with Artificial intelligence, Computer vision, Pattern recognition, Eye movement and Hidden Markov model. Artificial intelligence connects with themes related to Machine learning in his study. The concepts of his Computer vision study are interwoven with issues in Artificial neural network and Set.

His work on Image texture and Mixture model as part of his general Pattern recognition study is frequently connected to Generative model and Expectation–maximization algorithm, thereby bridging the divide between different branches of science. His research in Eye movement tackles topics such as Eye tracking which are related to areas like Fixation. His study looks at the intersection of Feature extraction and topics like Feature with Crowd counting.

He most often published in these fields:

  • Artificial intelligence (64.29%)
  • Computer vision (29.76%)
  • Pattern recognition (27.38%)

What were the highlights of his more recent work (between 2019-2021)?

  • Artificial intelligence (64.29%)
  • Computer vision (29.76%)
  • Eye movement (19.05%)

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

Antoni B. Chan mainly focuses on Artificial intelligence, Computer vision, Eye movement, Crowd counting and Pattern recognition. Many of his studies on Artificial intelligence involve topics that are commonly interrelated, such as Machine learning. His study in Computer vision is interdisciplinary in nature, drawing from both Heuristic and Flow network.

His research integrates issues of Cognitive psychology, Eye tracking and Hidden Markov model in his study of Eye movement. His work carried out in the field of Crowd counting brings together such families of science as Digit recognition and Discriminative model. His Image study combines topics from a wide range of disciplines, such as Deep learning and Representation.

Between 2019 and 2021, his most popular works were:

  • ROAM: Recurrently Optimizing Tracking Model (21 citations)
  • Visual Tracking via Dynamic Memory Networks (10 citations)
  • 3D Crowd Counting via Multi-View Fusion with 3D Gaussian Kernels (5 citations)

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

  • Artificial intelligence
  • Machine learning
  • Computer vision

Antoni B. Chan focuses on Artificial intelligence, Crowd counting, Computer vision, Object and Pattern recognition. While working on this project, Antoni B. Chan studies both Artificial intelligence and Gaussian function. In general Computer vision study, his work on Matching, Tracking and Object detection often relates to the realm of Trajectory, thereby connecting several areas of interest.

His Object research incorporates themes from Representation, Benchmark, Component and Interpolation. The Pattern recognition study combines topics in areas such as Property, Consistency and Projection. His research in Feature intersects with topics in Feature extraction, Memorization and Eye tracking.

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

Supervised Learning of Semantic Classes for Image Annotation and Retrieval

G. Carneiro;A.B. Chan;P.J. Moreno;N. Vasconcelos.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2007)

1120 Citations

Privacy preserving crowd monitoring: Counting people without people models or tracking

A.B. Chan;Z.-S.J. Liang;N. Vasconcelos.
computer vision and pattern recognition (2008)

910 Citations

Modeling, Clustering, and Segmenting Video with Mixtures of Dynamic Textures

A.B. Chan;N. Vasconcelos.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2008)

428 Citations

Counting People With Low-Level Features and Bayesian Regression

A. B. Chan;N. Vasconcelos.
IEEE Transactions on Image Processing (2012)

343 Citations

3D Human Pose Estimation from Monocular Images with Deep Convolutional Neural Network

Sijin Li;Antoni B. Chan.
asian conference on computer vision (2014)

335 Citations

On measuring the change in size of pulmonary nodules

A.P. Reeves;A.B. Chan;D.F. Yankelevitz;C.I. Henschke.
IEEE Transactions on Medical Imaging (2006)

264 Citations

Bayesian Poisson regression for crowd counting

Antoni B. Chan;Nuno Vasconcelos.
international conference on computer vision (2009)

259 Citations

Probabilistic kernels for the classification of auto-regressive visual processes

A.B. Chan;N. Vasconcelos.
computer vision and pattern recognition (2005)

203 Citations

System, Method and Apparatus for Small Pulmonary Nodule Computer Aided Diagnosis from Computed Tomography Scans

Anthony P. Reeves;David Yankelevitz;Claudia Henshke;Antoni Chan.
(2008)

199 Citations

Classifying Video with Kernel Dynamic Textures

A.B. Chan;N. Vasconcelos.
computer vision and pattern recognition (2007)

178 Citations

Best Scientists Citing Antoni B. Chan

Nuno Vasconcelos

Nuno Vasconcelos

University of California, San Diego

Publications: 32

Xiaogang Wang

Xiaogang Wang

Chinese University of Hong Kong

Publications: 26

David F. Yankelevitz

David F. Yankelevitz

Icahn School of Medicine at Mount Sinai

Publications: 26

Pascal Fua

Pascal Fua

École Polytechnique Fédérale de Lausanne

Publications: 26

Qi Wang

Qi Wang

Northwestern Polytechnical University

Publications: 24

Vishal M. Patel

Vishal M. Patel

Johns Hopkins University

Publications: 23

Claudia I. Henschke

Claudia I. Henschke

Icahn School of Medicine at Mount Sinai

Publications: 22

Mathieu Salzmann

Mathieu Salzmann

École Polytechnique Fédérale de Lausanne

Publications: 21

Gert R. G. Lanckriet

Gert R. G. Lanckriet

University of California, San Diego

Publications: 21

René Vidal

René Vidal

Johns Hopkins University

Publications: 19

Mubarak Shah

Mubarak Shah

University of Central Florida

Publications: 19

R. Venkatesh Babu

R. Venkatesh Babu

Indian Institute of Science Bangalore

Publications: 18

Nizar Bouguila

Nizar Bouguila

Concordia University

Publications: 17

Xuelong Li

Xuelong Li

Northwestern Polytechnical University

Publications: 16

Kostas Daniilidis

Kostas Daniilidis

University of Pennsylvania

Publications: 16

Chen Change Loy

Chen Change Loy

Nanyang Technological University

Publications: 15

Profile was last updated on December 6th, 2021.
Research.com Ranking is based on data retrieved from the Microsoft Academic Graph (MAG).
The ranking d-index is inferred from publications deemed to belong to the considered discipline.

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