The scientist’s investigation covers issues in Data mining, Visual analytics, Data visualization, Visualization and Artificial intelligence. The various areas that Tobias Schreck examines in his Data mining study include Feature extraction, Image retrieval and Cluster analysis. His Visual analytics research includes themes of Self-organizing map, Creative visualization, Analytics and Human–computer interaction.
His Data visualization study combines topics from a wide range of disciplines, such as Data science and Time series. His research investigates the connection between Visualization and topics such as Field that intersect with problems in Adjacency matrix, Data set and Graph drawing. The Artificial intelligence study combines topics in areas such as Machine learning, Scatter plot and Computer vision.
His primary areas of study are Visualization, Data mining, Visual analytics, Artificial intelligence and Information retrieval. He specializes in Visualization, namely Data visualization. His work in Data mining tackles topics such as Feature vector which are related to areas like Feature selection and Feature.
His research in Visual analytics tackles topics such as Data science which are related to areas like World Wide Web. His work deals with themes such as Machine learning, Computer vision and Pattern recognition, which intersect with Artificial intelligence. His studies deal with areas such as Object, Similarity and Visual Word as well as Information retrieval.
Tobias Schreck mainly focuses on Visual analytics, Visualization, Human–computer interaction, Artificial intelligence and Data visualization. His Visual analytics study necessitates a more in-depth grasp of Data mining. Tobias Schreck interconnects Drill down, Unsupervised learning and Time series in the investigation of issues within Data mining.
His work on Interactive visual analysis as part of general Visualization study is frequently linked to Set, therefore connecting diverse disciplines of science. Tobias Schreck has researched Artificial intelligence in several fields, including Machine learning, Computer vision and Pattern recognition. His Data visualization research incorporates elements of Data modeling, Identification, Relational database, Heuristic and Column.
His primary scientific interests are in Visual analytics, Visualization, Analytics, Data science and Data visualization. His Visual analytics study is concerned with the larger field of Artificial intelligence. His work in Visualization addresses issues such as Human–computer interaction, which are connected to fields such as Domain and Identification.
The concepts of his Analytics study are interwoven with issues in World Wide Web, Geospatial analysis, Data analysis and Big data. His Data science study incorporates themes from Industry 4.0, Data management, Computer graphics and Need to know. Tobias Schreck has included themes like Relational database and Cellular network in his Data visualization study.
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.
Visual analysis of large graphs : state-of-the-art and future research challenges
T. von Landesberger;A. Kuijper;A. Kuijper;T. Schreck;J. Kohlhammer.
Computer Graphics Forum (2011)
Feature-based similarity search in 3D object databases
Benjamin Bustos;Daniel A. Keim;Dietmar Saupe;Tobias Schreck.
ACM Computing Surveys (2005)
Visual cluster analysis of trajectory data with interactive Kohonen maps
Tobias Schreck;Jürgen Bernard;Tatiana Von Landesberger;Jörn Kohlhammer.
Information Visualization (2009)
Visual analytics for the big data era — A comparative review of state-of-the-art commercial systems
Leishi Zhang;Andreas Stoffel;Michael Behrisch;Sebastian Mittelstadt.
visual analytics science and technology (2012)
Space-in-time and time-in-space self-organizing maps for exploring spatiotemporal patterns
G. Andrienko;N. Andrienko;S. Bremm;T. Schreck.
ieee vgtc conference on visualization (2010)
Content-Based 3D Object Retrieval
B. Bustos;D. Keim;D. Saupe;T. Schreck.
IEEE Computer Graphics and Applications (2007)
Matrix reordering methods for table and network visualization
Michael Behrisch;Benjamin Bach;Nathalie Henry Riche;Tobias Schreck.
ieee vgtc conference on visualization (2016)
Overview of the ShARe/CLEF eHealth evaluation lab 2014
Liadh Kelly;Lorraine Goeuriot;Hanna Suominen;Tobias Schreck.
cross language evaluation forum (2014)
Sketch-based 3D model retrieval using diffusion tensor fields of suggestive contours
Sang Min Yoon;Maximilian Scherer;Tobias Schreck;Arjan Kuijper.
acm multimedia (2010)
A comparison of 3D shape retrieval methods based on a large-scale benchmark supporting multimodal queries
Bo Li;Yijuan Lu;Chunyuan Li;Afzal Godil.
Computer Vision and Image Understanding (2015)
Profile was last updated on December 6th, 2021.
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