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 55 Citations 50,140 90 World Ranking 2231 National Ranking 1189

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Computer vision
  • Machine learning

C. Lawrence Zitnick mainly focuses on Artificial intelligence, Image, Object detection, Computer vision and Closed captioning. His research ties Pattern recognition and Artificial intelligence together. His Object detection research focuses on Minimum bounding box and how it relates to Algorithm.

Computer vision is often connected to Pascal in his work. His Closed captioning study combines topics in areas such as Multimedia and Word. His work on Image segmentation as part of general Segmentation study is frequently linked to User interface, therefore connecting diverse disciplines of science.

His most cited work include:

  • Microsoft COCO: Common Objects in Context (10541 citations)
  • Microsoft COCO: Common Objects in Context (3312 citations)
  • Edge Boxes: Locating Object Proposals from Edges (1994 citations)

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

C. Lawrence Zitnick mainly focuses on Artificial intelligence, Computer vision, Pattern recognition, Image and Natural language processing. His Object detection, Segmentation and Closed captioning study in the realm of Artificial intelligence interacts with subjects such as Task. The Computer vision study which covers Compressed sensing that intersects with Deep learning and End-to-end principle.

The various areas that he examines in his Image study include Sentence, Embedding and Convolutional neural network. His work on Noun as part of general Natural language processing research is frequently linked to Metric, bridging the gap between disciplines. His research investigates the link between Cognitive neuroscience of visual object recognition and topics such as Pascal that cross with problems in Spotting and Minimum bounding box.

He most often published in these fields:

  • Artificial intelligence (76.15%)
  • Computer vision (30.28%)
  • Pattern recognition (22.94%)

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

  • Artificial intelligence (76.15%)
  • Machine learning (12.84%)
  • Computer vision (30.28%)

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

C. Lawrence Zitnick mainly investigates Artificial intelligence, Machine learning, Computer vision, Parallel imaging and Deep learning. His work on Artificial intelligence deals in particular with Iterative reconstruction and Image quality. His work deals with themes such as Language model and Representation, which intersect with Machine learning.

The study incorporates disciplines such as Variation and Domain knowledge in addition to Representation. C. Lawrence Zitnick performs integrative study on Computer vision and Signal processing. His Deep learning study frequently intersects with other fields, such as Pattern recognition.

Between 2018 and 2021, his most popular works were:

  • Biological Structure and Function Emerge from Scaling Unsupervised Learning to 250 Million Protein Sequences (110 citations)
  • fastMRI: A Publicly Available Raw k-Space and DICOM Dataset of Knee Images for Accelerated MR Image Reconstruction Using Machine Learning. (35 citations)
  • ELF OpenGo: An Analysis and Open Reimplementation of AlphaZero (34 citations)

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

  • Artificial intelligence
  • Computer vision
  • Machine learning

His main research concerns Artificial intelligence, Computer vision, Parallel imaging, Mr images and Iterative reconstruction. C. Lawrence Zitnick frequently studies issues relating to Machine learning and Artificial intelligence. In general Machine learning study, his work on Unsupervised learning often relates to the realm of Sequence, thereby connecting several areas of interest.

C. Lawrence Zitnick conducts interdisciplinary study in the fields of Computer vision and Signal processing through his research. As part of his studies on Mr images, C. Lawrence Zitnick frequently links adjacent subjects like k-space. His Iterative reconstruction research includes elements of Artificial neural network and Deep learning.

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

Microsoft COCO: Common Objects in Context

Tsung-Yi Lin;Michael Maire;Serge J. Belongie;James Hays.
european conference on computer vision (2014)

11403 Citations

Microsoft COCO: Common Objects in Context

Tsung-Yi Lin;Michael Maire;Serge Belongie;Lubomir Bourdev.
arXiv: Computer Vision and Pattern Recognition (2014)

6948 Citations

VQA: Visual Question Answering

Stanislaw Antol;Aishwarya Agrawal;Jiasen Lu;Margaret Mitchell.
international conference on computer vision (2015)

2676 Citations

Edge Boxes: Locating Object Proposals from Edges

C. Lawrence Zitnick;Piotr Dollár.
european conference on computer vision (2014)

2652 Citations

CIDEr: Consensus-based image description evaluation

Ramakrishna Vedantam;C. Lawrence Zitnick;Devi Parikh.
computer vision and pattern recognition (2015)

1731 Citations

High-quality video view interpolation using a layered representation

C. Lawrence Zitnick;Sing Bing Kang;Matthew Uyttendaele;Simon Winder.
international conference on computer graphics and interactive techniques (2004)

1722 Citations

VQA: Visual Question Answering

Aishwarya Agrawal;Jiasen Lu;Stanislaw Antol;Margaret Mitchell.
arXiv: Computation and Language (2015)

1635 Citations

Microsoft COCO Captions: Data Collection and Evaluation Server

Xinlei Chen;Hao Fang;Tsung-Yi Lin;Ramakrishna Vedantam.
arXiv: Computer Vision and Pattern Recognition (2015)

1181 Citations

Structured Forests for Fast Edge Detection

Piotr Dollar;C. Lawrence Zitnick.
international conference on computer vision (2013)

1019 Citations

From captions to visual concepts and back

Hao Fang;Saurabh Gupta;Forrest Iandola;Rupesh K. Srivastava.
computer vision and pattern recognition (2015)

900 Citations

Best Scientists Citing C. Lawrence Zitnick

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Chunhua Shen

Chunhua Shen

University of Adelaide

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Xiaogang Wang

Xiaogang Wang

Chinese University of Hong Kong

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Trevor Darrell

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University of California, Berkeley

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Alan L. Yuille

Alan L. Yuille

Johns Hopkins University

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Dhruv Batra

Dhruv Batra

Georgia Institute of Technology

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Ming-Hsuan Yang

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Wanli Ouyang

Wanli Ouyang

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Anton van den Hengel

Anton van den Hengel

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Marcus Rohrbach

Marcus Rohrbach

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Li Fei-Fei

Li Fei-Fei

Stanford University

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Ross Girshick

Ross Girshick

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Ali Farhadi

Ali Farhadi

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Bernt Schiele

Bernt Schiele

Max Planck Institute for Informatics

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Liang Lin

Liang Lin

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Kaiming He

Kaiming He

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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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