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.
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.
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.
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.
Evaluation of Interest Point Detectors
Cordelia Schmid;Roger Mohr;Christian Bauckhage.
International Journal of Computer Vision (2000)
The slashdot zoo: mining a social network with negative edges
Jérôme Kunegis;Andreas Lommatzsch;Christian Bauckhage.
the web conference (2009)
Comparing and evaluating interest points
C. Schmid;R. Mohr;C. Bauckhage.
international conference on computer vision (1998)
Informed Haar-Like Features Improve Pedestrian Detection
Shanshan Zhang;Christian Bauckhage;Armin B. Cremers.
computer vision and pattern recognition (2014)
Insights into Internet Memes
international conference on weblogs and social media (2011)
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)
Loveparade 2010: Automatic video analysis of a crowd disaster
Barbara Krausz;Christian Bauckhage.
Computer Vision and Image Understanding (2012)
Predicting player churn in the wild
Fabian Hadiji;Rafet Sifa;Anders Drachen;Christian Thurau.
computational intelligence and games (2014)
I tag, you tag: translating tags for advanced user models
Robert Wetzker;Carsten Zimmermann;Christian Bauckhage;Sahin Albayrak.
web search and data mining (2010)
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)
Profile was last updated on December 6th, 2021.
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