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 46 Citations 13,947 180 World Ranking 3449 National Ranking 12

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Machine learning
  • Computer vision

Artificial intelligence, Computer vision, Benchmark, Tracking and Video tracking are his primary areas of study. His Artificial intelligence study incorporates themes from Machine learning and Pattern recognition. He has included themes like Computational complexity theory and Representation in his Computer vision study.

His Benchmark course of study focuses on Deep learning and Variety. His studies deal with areas such as Algorithm and Sparse approximation as well as Tracking. His study in Video tracking is interdisciplinary in nature, drawing from both Ground truth, Eye tracking and Pattern recognition.

His most cited work include:

  • ActivityNet: A large-scale video benchmark for human activity understanding (1057 citations)
  • Robust visual tracking via multi-task sparse learning (576 citations)
  • A Benchmark and Simulator for UAV Tracking (562 citations)

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

His primary areas of study are Artificial intelligence, Computer vision, Pattern recognition, Machine learning and Robustness. In general Artificial intelligence study, his work on Video tracking, Object detection, Deep learning and Benchmark often relates to the realm of Action, thereby connecting several areas of interest. His research in Video tracking intersects with topics in Particle filter and Eye tracking.

His Machine learning study often links to related topics such as Question answering. His biological study deals with issues like Algorithm, which deal with fields such as Nonlinear system. His Tracking research focuses on subjects like Sparse approximation, which are linked to Representation.

He most often published in these fields:

  • Artificial intelligence (70.71%)
  • Computer vision (21.76%)
  • Pattern recognition (19.67%)

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

  • Artificial intelligence (70.71%)
  • Pattern recognition (19.67%)
  • Point cloud (9.21%)

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

The scientist’s investigation covers issues in Artificial intelligence, Pattern recognition, Point cloud, Segmentation and Theoretical computer science. As a member of one scientific family, Bernard Ghanem mostly works in the field of Artificial intelligence, focusing on Machine learning and, on occasion, Robustness. The Pattern recognition study combines topics in areas such as Generator, Image, Face and Task.

As part of one scientific family, Bernard Ghanem deals mainly with the area of Point cloud, narrowing it down to issues related to the Distributed computing, and often Robot. His Segmentation research incorporates themes from Kernel and Benchmark. Bernard Ghanem interconnects Affine transformation, Feature learning, Convex hull and Graph in the investigation of issues within Theoretical computer science.

Between 2019 and 2021, his most popular works were:

  • DeeperGCN: All You Need to Train Deeper GCNs (42 citations)
  • G-TAD: Sub-Graph Localization for Temporal Action Detection (41 citations)
  • SGAS: Sequential Greedy Architecture Search (35 citations)

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

  • Artificial intelligence
  • Machine learning
  • Computer vision

His primary areas of study are Artificial intelligence, Graph, Theoretical computer science, Adversarial system and Feature extraction. His biological study spans a wide range of topics, including Machine learning and Pattern recognition. His Machine learning research includes elements of Modality and Correlation.

His Graph study combines topics in areas such as Convolutional neural network and Feature vector. His Adversarial system research is multidisciplinary, relying on both Distributed computing and Robustness. His work focuses on many connections between Feature extraction and other disciplines, such as Image resolution, that overlap with his field of interest in Pixel.

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

The Visual Object Tracking VOT2016 Challenge Results

Matej Kristan;Aleš Leonardis;Jiři Matas;Michael Felsberg.
european conference on computer vision (2016)

1423 Citations

ActivityNet: A large-scale video benchmark for human activity understanding

Fabian Caba Heilbron;Victor Escorcia;Bernard Ghanem;Juan Carlos Niebles.
computer vision and pattern recognition (2015)

1129 Citations

Robust visual tracking via multi-task sparse learning

Tianzhu Zhang;Bernard Ghanem;Si Liu;Narendra Ahuja.
computer vision and pattern recognition (2012)

771 Citations

A Benchmark and Simulator for UAV Tracking

Matthias Mueller;Neil Smith;Bernard Ghanem.
european conference on computer vision (2016)

669 Citations

Context-Aware Correlation Filter Tracking

Matthias Mueller;Neil Smith;Bernard Ghanem.
computer vision and pattern recognition (2017)

475 Citations

Robust Visual Tracking via Structured Multi-Task Sparse Learning

Tianzhu Zhang;Bernard Ghanem;Si Liu;Narendra Ahuja.
International Journal of Computer Vision (2013)

358 Citations

DAPs: Deep Action Proposals for Action Understanding

Victor Escorcia;Fabian Caba Heilbron;Juan Carlos Niebles;Juan Carlos Niebles;Bernard Ghanem.
european conference on computer vision (2016)

307 Citations

SST: Single-Stream Temporal Action Proposals

Shyamal Buch;Victor Escorcia;Chuanqi Shen;Bernard Ghanem.
computer vision and pattern recognition (2017)

283 Citations

Low-rank sparse learning for robust visual tracking

Tianzhu Zhang;Bernard Ghanem;Si Liu;Narendra Ahuja.
european conference on computer vision (2012)

260 Citations

Robust Visual Tracking Via Consistent Low-Rank Sparse Learning

Tianzhu Zhang;Si Liu;Narendra Ahuja;Ming-Hsuan Yang.
International Journal of Computer Vision (2015)

256 Citations

Best Scientists Citing Bernard Ghanem

Ming-Hsuan Yang

Ming-Hsuan Yang

University of California, Merced

Publications: 64

Huchuan Lu

Huchuan Lu

Dalian University of Technology

Publications: 45

Luc Van Gool

Luc Van Gool

ETH Zurich

Publications: 38

Haibin Ling

Haibin Ling

Stony Brook University

Publications: 36

Wei Liu

Wei Liu

Tencent (China)

Publications: 36

Tianzhu Zhang

Tianzhu Zhang

University of Science and Technology of China

Publications: 35

Changsheng Xu

Changsheng Xu

Chinese Academy of Sciences

Publications: 32

Fatih Porikli

Fatih Porikli

Australian National University

Publications: 32

Jiebo Luo

Jiebo Luo

University of Rochester

Publications: 32

Dong Wang

Dong Wang

Dalian University of Technology

Publications: 28

Qi Tian

Qi Tian

Huawei Technologies (China)

Publications: 28

Larry S. Davis

Larry S. Davis

University of Maryland, College Park

Publications: 28

Fahad Shahbaz Khan

Fahad Shahbaz Khan

Zayed University

Publications: 27

Dahua Lin

Dahua Lin

Chinese University of Hong Kong

Publications: 26

Martin Danelljan

Martin Danelljan

ETH Zurich

Publications: 25

Weiming Hu

Weiming Hu

Chinese Academy of Sciences

Publications: 24

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.

If you think any of the details on this page are incorrect, let us know.

Contact us
Something went wrong. Please try again later.