Cláudio T. Silva mostly deals with Visualization, Artificial intelligence, Data visualization, Rendering and Algorithm. His biological study spans a wide range of topics, including World Wide Web, Computer graphics, Workflow and Human–computer interaction. The concepts of his Artificial intelligence study are interwoven with issues in Manifold, Machine learning, Computer vision and Surface reconstruction.
His work carried out in the field of Data visualization brings together such families of science as Software system, Projection, Pipeline, Analytics and Component. In his research on the topic of Rendering, Differential geometry and Point set is strongly related with Frame rate. The study incorporates disciplines such as Point cloud, Mesh generation and Theoretical computer science in addition to Algorithm.
Visualization, Data visualization, Data science, Computer graphics and Artificial intelligence are his primary areas of study. His Visualization research includes themes of Analytics and Human–computer interaction. His work deals with themes such as Data modeling, Theoretical computer science and Computer graphics, which intersect with Data visualization.
His Data science research is multidisciplinary, incorporating elements of World Wide Web, Data management, Workflow and Interactive visualization. His research integrates issues of Mesh generation and Computational geometry in his study of Computer graphics. His Artificial intelligence study integrates concerns from other disciplines, such as Algorithm, Machine learning, Computer vision and Pattern recognition.
Cláudio T. Silva focuses on Visualization, Artificial intelligence, Data visualization, Visual analytics and Data science. His studies in Visualization integrate themes in fields like Feature extraction, Computer graphics and Human–computer interaction. His studies deal with areas such as Detector, Construct, Computer vision, Machine learning and Pattern recognition as well as Artificial intelligence.
Cláudio T. Silva studied Data visualization and Variety that intersect with Use case. His Visual analytics research is multidisciplinary, relying on both Motion, Pipeline and Set. His Data science research is multidisciplinary, incorporating perspectives in Data management, Offensive and Identification.
His main research concerns Data visualization, Artificial intelligence, Visualization, Visual analytics and Data mining. His Data visualization research integrates issues from Programming language and Data science. Cláudio T. Silva has researched Artificial intelligence in several fields, including Machine learning, Computer vision and Surface reconstruction.
His work in Surface reconstruction covers topics such as Algorithm which are related to areas like Parametrization. The Visualization study combines topics in areas such as Data flow diagram, Feature extraction and Computer graphics, Computer graphics. His Information visualization research incorporates themes from Data modeling, Timeline, Row and Rendering.
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Computing and rendering point set surfaces
M. Alexa;J. Behr;D. Cohen-Or;S. Fleishman.
IEEE Transactions on Visualization and Computer Graphics (2003)
The ball-pivoting algorithm for surface reconstruction
F. Bernardini;J. Mittleman;H. Rushmeier;C. Silva.
IEEE Transactions on Visualization and Computer Graphics (1999)
Point set surfaces
Marc Alexa;Johannes Behr;Daniel Cohen-Or;Shachar Fleishman.
ieee visualization (2001)
Provenance for Computational Tasks: A Survey
J. Freire;D. Koop;E. Santos;C.T. Silva.
computational science and engineering (2008)
VisTrails: visualization meets data management
Steven P. Callahan;Juliana Freire;Emanuele Santos;Carlos E. Scheidegger.
international conference on management of data (2006)
Robust moving least-squares fitting with sharp features
Shachar Fleishman;Daniel Cohen-Or;Cláudio T. Silva.
international conference on computer graphics and interactive techniques (2005)
A survey of visibility for walkthrough applications
D. Cohen-Or;Y.L. Chrysanthou;C.T. Silva;F. Durand.
IEEE Transactions on Visualization and Computer Graphics (2003)
Visual Exploration of Big Spatio-Temporal Urban Data: A Study of New York City Taxi Trips
Nivan Ferreira;Jorge Poco;Huy T. Vo;Juliana Freire.
IEEE Transactions on Visualization and Computer Graphics (2013)
The ALPS project release 2.0: open source software for strongly correlated systems
B. Bauer;L.D. Carr;Hans Gerd Evertz;A. Feiguin.
Journal of Statistical Mechanics: Theory and Experiment (2011)
VisTrails: enabling interactive multiple-view visualizations
L. Bavoil;S.P. Callahan;P.J. Crossno;J. Freire.
ieee visualization (2005)
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