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 11,259 121 World Ranking 4579 National Ranking 121

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Machine learning
  • Computer vision

Stephen Gould mainly focuses on Artificial intelligence, Computer vision, Pattern recognition, Image and Closed captioning. He usually deals with Artificial intelligence and limits it to topics linked to Machine learning and Connected-component labeling. His work on Object and Face as part of general Computer vision research is often related to Clutter, thus linking different fields of science.

His study explores the link between Pattern recognition and topics such as Image processing that cross with problems in Minimum spanning tree-based segmentation. His Image research is multidisciplinary, relying on both Range, Speech recognition, Word and State. His Closed captioning study combines topics in areas such as Question answering, Natural language processing, Feature and Feature vector.

His most cited work include:

  • Bottom-Up and Top-Down Attention for Image Captioning and Visual Question Answering (1510 citations)
  • SPICE: Semantic Propositional Image Caption Evaluation (641 citations)
  • Decomposing a scene into geometric and semantically consistent regions (582 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 Image. His works in Segmentation, Object, Image segmentation, Deep learning and Benchmark are all subjects of inquiry into Artificial intelligence. His studies deal with areas such as Feature and Pooling as well as Pattern recognition.

His Machine learning study which covers Inference that intersects with Pairwise comparison. He works in the field of Image, namely Closed captioning. The concepts of his Closed captioning study are interwoven with issues in Question answering, Natural language processing and State.

He most often published in these fields:

  • Artificial intelligence (70.79%)
  • Computer vision (26.40%)
  • Pattern recognition (25.84%)

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

  • Artificial intelligence (70.79%)
  • Benchmark (8.43%)
  • Machine learning (16.29%)

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

Stephen Gould focuses on Artificial intelligence, Benchmark, Machine learning, Natural language and Algorithm. His work carried out in the field of Artificial intelligence brings together such families of science as Key and Natural language processing. Within one scientific family, Stephen Gould focuses on topics pertaining to Inference under Machine learning, and may sometimes address concerns connected to Probabilistic automaton, Generative grammar and Latent variable.

His Natural language research includes themes of Test, Ontology and Human–computer interaction. Stephen Gould has researched Algorithm in several fields, including Artificial neural network, Point cloud, Perspective and Ground truth. His Object research integrates issues from Spatial analysis, Adjacency list and Pattern recognition.

Between 2019 and 2021, his most popular works were:

  • A Signal Propagation Perspective for Pruning Neural Networks at Initialization (36 citations)
  • Proposal-free Temporal Moment Localization of a Natural-Language Query in Video using Guided Attention (25 citations)
  • A Stochastic Conditioning Scheme for Diverse Human Motion Prediction (12 citations)

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

  • Artificial intelligence
  • Machine learning
  • Statistics

Stephen Gould mainly investigates Artificial intelligence, Benchmark, Natural language, Machine learning and Key. His studies in Artificial intelligence integrate themes in fields like Algorithm and Partially observable Markov decision process. The various areas that he examines in his Benchmark study include Test, Traceability and Human–computer interaction.

His research in Natural language intersects with topics in Ontology and Robotics, Robotic mapping. His Pruning and Artificial neural network study in the realm of Machine learning connects with subjects such as Initialization and Sensitivity. His work deals with themes such as Object, Segmentation, Deep learning and Pose, which intersect with Key.

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

Bottom-Up and Top-Down Attention for Image Captioning and Visual Question Answering

Peter Anderson;Xiaodong He;Chris Buehler;Damien Teney.
computer vision and pattern recognition (2018)

1704 Citations

Decomposing a scene into geometric and semantically consistent regions

Stephen Gould;Richard Fulton;Daphne Koller.
international conference on computer vision (2009)

743 Citations

SPICE: Semantic Propositional Image Caption Evaluation

Peter Anderson;Basura Fernando;Mark Johnson;Stephen Gould.
european conference on computer vision (2016)

646 Citations

Dynamic Image Networks for Action Recognition

Hakan Bilen;Basura Fernando;Efstratios Gavves;Andrea Vedaldi.
computer vision and pattern recognition (2016)

501 Citations

Single image depth estimation from predicted semantic labels

Beyang Liu;Stephen Gould;Daphne Koller.
computer vision and pattern recognition (2010)

491 Citations

Multi-Class Segmentation with Relative Location Prior

Stephen Gould;Jim Rodgers;David Cohen;Gal Elidan.
International Journal of Computer Vision (2008)

471 Citations

Bottom-Up and Top-Down Attention for Image Captioning and VQA.

Peter Anderson;Xiaodong He;Chris Buehler;Damien Teney.
(2017)

330 Citations

Vision-and-Language Navigation: Interpreting Visually-Grounded Navigation Instructions in Real Environments

Peter Anderson;Qi Wu;Damien Teney;Jake Bruce.
computer vision and pattern recognition (2018)

247 Citations

Self-Supervised Video Representation Learning with Odd-One-Out Networks

Basura Fernando;Hakan Bilen;Efstratios Gavves;Stephen Gould.
computer vision and pattern recognition (2017)

241 Citations

Region-based Segmentation and Object Detection

Stephen Gould;Tianshi Gao;Daphne Koller.
neural information processing systems (2009)

222 Citations

Best Scientists Citing Stephen Gould

Dhruv Batra

Dhruv Batra

Georgia Institute of Technology

Publications: 68

Devi Parikh

Devi Parikh

Facebook (United States)

Publications: 63

Alexander G. Schwing

Alexander G. Schwing

University of Illinois at Urbana-Champaign

Publications: 39

Hanwang Zhang

Hanwang Zhang

Nanyang Technological University

Publications: 36

Philip H. S. Torr

Philip H. S. Torr

University of Oxford

Publications: 34

Anton van den Hengel

Anton van den Hengel

University of Adelaide

Publications: 33

Stefan Lee

Stefan Lee

Oregon State University

Publications: 33

Jiebo Luo

Jiebo Luo

University of Rochester

Publications: 32

Mathieu Salzmann

Mathieu Salzmann

École Polytechnique Fédérale de Lausanne

Publications: 32

Andrew Zisserman

Andrew Zisserman

University of Oxford

Publications: 31

Luc Van Gool

Luc Van Gool

ETH Zurich

Publications: 30

Chunhua Shen

Chunhua Shen

University of Adelaide

Publications: 29

Dacheng Tao

Dacheng Tao

University of Sydney

Publications: 29

Jianfei Cai

Jianfei Cai

Monash University

Publications: 29

Ali Farhadi

Ali Farhadi

University of Washington

Publications: 28

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.