H-Index & Metrics Top Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Computer Science H-index 49 Citations 22,411 250 World Ranking 3039 National Ranking 31

Research.com Recognitions

Awards & Achievements

2012 - ACM Senior Member

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Machine learning
  • Statistics

Information retrieval, Artificial intelligence, TRECVID, Search engine indexing and Image retrieval are his primary areas of study. His study in the field of Ontology is also linked to topics like Social image. His studies deal with areas such as Machine learning, Computer vision and Pattern recognition as well as Artificial intelligence.

His Search engine indexing research is multidisciplinary, incorporating elements of Image processing, Ranking, Multimedia and Modality. His Content-based image retrieval and Visual Word study, which is part of a larger body of work in Image retrieval, is frequently linked to Set, bridging the gap between disciplines. His research investigates the link between Content-based image retrieval and topics such as Automatic image annotation that cross with problems in Multimedia information retrieval, Semantic interpretation, Semantic gap and Relevance feedback.

His most cited work include:

  • Content-based image retrieval at the end of the early years (5505 citations)
  • Early versus late fusion in semantic video analysis (649 citations)
  • The challenge problem for automated detection of 101 semantic concepts in multimedia (555 citations)

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

His scientific interests lie mostly in Artificial intelligence, Information retrieval, Multimedia, Search engine indexing and Computer vision. His research in Artificial intelligence focuses on subjects like Machine learning, which are connected to Representation, Relevance feedback and Classifier. His Information retrieval research is multidisciplinary, incorporating perspectives in Image, Image retrieval, Information visualization and TRECVID.

Image retrieval connects with themes related to Image processing in his study. His work focuses on many connections between Multimedia and other disciplines, such as Analytics, that overlap with his field of interest in Cultural analytics. Search engine indexing is closely attributed to Feature extraction in his research.

He most often published in these fields:

  • Artificial intelligence (35.85%)
  • Information retrieval (35.01%)
  • Multimedia (22.97%)

What were the highlights of his more recent work (between 2017-2021)?

  • Artificial intelligence (35.85%)
  • Machine learning (10.64%)
  • Interactive Learning (3.64%)

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

His primary areas of study are Artificial intelligence, Machine learning, Interactive Learning, Relevance feedback and Information retrieval. His research in Artificial intelligence tackles topics such as Natural language processing which are related to areas like Pipeline, Feature and Closed captioning. His work deals with themes such as Classifier, Scalability and Search engine indexing, which intersect with Interactive Learning.

Marcel Worring has included themes like External Data Representation, Mobile device and Key in his Search engine indexing study. His Relevance feedback research integrates issues from Multimodal learning, Multimedia, State and Human–computer interaction. His biological study spans a wide range of topics, including Generator and Benchmark.

Between 2017 and 2021, his most popular works were:

  • OmniArt: A Large-scale Artistic Benchmark (30 citations)
  • BERT for Evidence Retrieval and Claim Verification (23 citations)
  • Many Task Learning With Task Routing (23 citations)

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

  • Artificial intelligence
  • Machine learning
  • Statistics

Marcel Worring spends much of his time researching Artificial intelligence, Interactive Learning, Relevance feedback, State and Machine learning. His Artificial intelligence research is multidisciplinary, incorporating perspectives in Hypergraph, Information retrieval and Pattern recognition. His Information retrieval research incorporates themes from Cognitive neuroscience of visual object recognition, Metadata, Color space, Point and Benchmark.

The concepts of his Interactive Learning study are interwoven with issues in Scalability and Search engine indexing. The Search engine indexing study combines topics in areas such as Multimedia and Mobile device. Marcel Worring interconnects Multimodal learning and Relevance in the investigation of issues within Relevance feedback.

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.

Top Publications

Content-based image retrieval at the end of the early years

A.W.M. Smeulders;M. Worring;S. Santini;A. Gupta.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2000)

8121 Citations

ICDAR 2003 robust reading competitions: entries, results, and future directions

Simon M. Lucas;Alex Panaretos;Luis Sosa;Anthony Tang.
International Journal on Document Analysis and Recognition (2005)

935 Citations

Early versus late fusion in semantic video analysis

Cees G. M. Snoek;Marcel Worring;Arnold W. M. Smeulders.
acm multimedia (2005)

893 Citations

The challenge problem for automated detection of 101 semantic concepts in multimedia

Cees G. M. Snoek;Marcel Worring;Jan C. van Gemert;Jan-Mark Geusebroek.
acm multimedia (2006)

727 Citations

Multimodal Video Indexing: A Review of the State-of-the-art

Cees G. M. Snoek;Marcel Worring.
Multimedia Tools and Applications (2005)

713 Citations

Learning Social Tag Relevance by Neighbor Voting

Xirong Li;C.G.M. Snoek;M. Worring.
IEEE Transactions on Multimedia (2009)

459 Citations

Concept-Based Video Retrieval

Cees G. M. Snoek;Marcel Worring.
(2009)

451 Citations

NIST Special Publication

C.G.M. Snoek;M. Worring;J.M. Geusebroek;D.C. Koelma.
(2005)

438 Citations

The MediaMill TRECVID 2007 Semantic Video Search Engine

C. Snoek;I. Everts;van J.C. Gemert;Jan-Mark Geusebroek.
Proceedings of the 5th TRECVID Workshop (2007)

435 Citations

The MediaMill TRECVID 2010 semantic video search engine

C.G.M. Snoek;K.E.A. van de Sande;O. de Rooij;B. Huurnink.
TRECVID Workshop (2010)

434 Citations

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

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Top Scientists Citing Marcel Worring

Gerald Schaefer

Gerald Schaefer

Loughborough University

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Henning Müller

Henning Müller

University of Applied Sciences and Arts Western Switzerland

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Alexander G. Hauptmann

Alexander G. Hauptmann

Carnegie Mellon University

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Jianping Fan

Jianping Fan

University of North Carolina at Charlotte

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Qi Tian

Qi Tian

Huawei Technologies (China)

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Cees G. M. Snoek

Cees G. M. Snoek

University of Amsterdam

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Ioannis Kompatsiaris

Ioannis Kompatsiaris

Information Technologies Institute, Greece

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Meng Wang

Meng Wang

Hefei University of Technology

Publications: 54

Tat-Seng Chua

Tat-Seng Chua

National University of Singapore

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Xian-Sheng Hua

Xian-Sheng Hua

Microsoft (United States)

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Arnold W. M. Smeulders

Arnold W. M. Smeulders

University of Amsterdam

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Alan F. Smeaton

Alan F. Smeaton

Dublin City University

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Joemon M. Jose

Joemon M. Jose

University of Glasgow

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Alberto Del Bimbo

Alberto Del Bimbo

University of Florence

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Jiebo Luo

Jiebo Luo

University of Rochester

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