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 43 Citations 9,473 220 World Ranking 3956 National Ranking 183

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Machine learning
  • Statistics

Christian Bauckhage mostly deals with Artificial intelligence, Machine learning, Pattern recognition, Data mining and World Wide Web. Christian Bauckhage integrates Artificial intelligence with Simulations and games in economics education in his study. The study incorporates disciplines such as Context and Maximization in addition to Machine learning.

Christian Bauckhage combines subjects such as Vector space and Computer vision with his study of Pattern recognition. Christian Bauckhage has researched Data mining in several fields, including Non-negative matrix factorization, Clustering coefficient, Cluster analysis and Pattern recognition. Christian Bauckhage works mostly in the field of Content, limiting it down to concerns involving Simulation and, occasionally, Repeatability, Interest point detection and Behavioral analytics.

His most cited work include:

  • Evaluation of Interest Point Detectors (1366 citations)
  • The slashdot zoo: mining a social network with negative edges (388 citations)
  • Comparing and evaluating interest points (262 citations)

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

Artificial intelligence, Machine learning, Pattern recognition, Computer vision and Cluster analysis are his primary areas of study. In his work, Cognition is strongly intertwined with Human–computer interaction, which is a subfield of Artificial intelligence. His biological study spans a wide range of topics, including Video game development, Probabilistic logic, Key and Robustness.

His Computer vision research includes themes of Pedestrian detection and Support vector machine. Christian Bauckhage frequently studies issues relating to Data mining and Cluster analysis. His studies in Data mining integrate themes in fields like Matrix decomposition and Non-negative matrix factorization.

He most often published in these fields:

  • Artificial intelligence (57.14%)
  • Machine learning (19.29%)
  • Pattern recognition (16.07%)

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

  • Artificial intelligence (57.14%)
  • Machine learning (19.29%)
  • Algorithm (6.79%)

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

Christian Bauckhage mainly investigates Artificial intelligence, Machine learning, Algorithm, Recurrent neural network and Natural language processing. His Artificial intelligence study frequently links to related topics such as Context. His research in Machine learning intersects with topics in Segmentation and Robustness.

His work carried out in the field of Algorithm brings together such families of science as Energy minimization and Kernel. His Recurrent neural network research is multidisciplinary, relying on both Distributed computing, Parametric statistics and Sequence labeling. He interconnects Gradient descent and Embedding in the investigation of issues within Natural language processing.

Between 2018 and 2021, his most popular works were:

  • Informed Machine Learning -- A Taxonomy and Survey of Integrating Knowledge into Learning Systems (26 citations)
  • Informed Machine Learning - Towards a Taxonomy of Explicit Integration of Knowledge into Machine Learning. (16 citations)
  • Triple Classification Using Regions and Fine-Grained Entity Typing (14 citations)

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

  • Artificial intelligence
  • Machine learning
  • Statistics

His scientific interests lie mostly in Artificial intelligence, Machine learning, Algorithm, Recurrent neural network and Context. His Artificial intelligence study frequently draws parallels with other fields, such as Task. His Machine learning study incorporates themes from Field, Representation, Key and Taxonomy.

His study in Algorithm is interdisciplinary in nature, drawing from both Gaussian and Kernel. His Recurrent neural network research includes elements of Binary classification, Language model and Subject-matter expert. As a part of the same scientific family, he mostly works in the field of Context, focusing on Machine translation and, on occasion, Sentence.

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

Evaluation of Interest Point Detectors

Cordelia Schmid;Roger Mohr;Christian Bauckhage.
International Journal of Computer Vision (2000)

2290 Citations

The slashdot zoo: mining a social network with negative edges

Jérôme Kunegis;Andreas Lommatzsch;Christian Bauckhage.
the web conference (2009)

519 Citations

Comparing and evaluating interest points

C. Schmid;R. Mohr;C. Bauckhage.
international conference on computer vision (1998)

496 Citations

Informed Haar-Like Features Improve Pedestrian Detection

Shanshan Zhang;Christian Bauckhage;Armin B. Cremers.
computer vision and pattern recognition (2014)

350 Citations

Insights into Internet Memes

Christian Bauckhage.
international conference on weblogs and social media (2011)

244 Citations

Guns, swords and data: Clustering of player behavior in computer games in the wild

Anders Drachen;Rafet Sifa;Christian Bauckhage;Christian Thurau.
computational intelligence and games (2012)

186 Citations

Loveparade 2010: Automatic video analysis of a crowd disaster

Barbara Krausz;Christian Bauckhage.
Computer Vision and Image Understanding (2012)

173 Citations

Predicting player churn in the wild

Fabian Hadiji;Rafet Sifa;Anders Drachen;Christian Thurau.
computational intelligence and games (2014)

156 Citations

I tag, you tag: translating tags for advanced user models

Robert Wetzker;Carsten Zimmermann;Christian Bauckhage;Sahin Albayrak.
web search and data mining (2010)

141 Citations

Early drought stress detection in cereals: simplex volume maximisation for hyperspectral image analysis

Christoph Römer;Mirwaes Wahabzada;Agim Ballvora;Francisco Pinto.
Functional Plant Biology (2012)

136 Citations

Best Scientists Citing Christian Bauckhage

Gerhard Sagerer

Gerhard Sagerer

Bielefeld University

Publications: 29

Georgios N. Yannakakis

Georgios N. Yannakakis

University of Malta

Publications: 21

Julian Togelius

Julian Togelius

New York University

Publications: 21

Kristian Kersting

Kristian Kersting

TU Darmstadt

Publications: 20

Rajarshi Gupta

Rajarshi Gupta

Amazon Web Services

Publications: 18

In So Kweon

In So Kweon

Korea Advanced Institute of Science and Technology

Publications: 17

Nicu Sebe

Nicu Sebe

University of Trento

Publications: 14

Xuelong Li

Xuelong Li

Northwestern Polytechnical University

Publications: 14

Bernt Schiele

Bernt Schiele

Max Planck Institute for Informatics

Publications: 14

Helge Ritter

Helge Ritter

Bielefeld University

Publications: 14

Cordelia Schmid

Cordelia Schmid

French Institute for Research in Computer Science and Automation - INRIA

Publications: 13

Jiliang Tang

Jiliang Tang

Michigan State University

Publications: 12

Chandra Kambhamettu

Chandra Kambhamettu

University of Delaware

Publications: 12

Diego Klabjan

Diego Klabjan

Northwestern University

Publications: 11

Abdulmotaleb El Saddik

Abdulmotaleb El Saddik

University of Ottawa

Publications: 10

Simon Lacroix

Simon Lacroix

Federal University of Toulouse Midi-Pyrénées

Publications: 10

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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