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» Learning computing models from cells and tissues: P systems
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NIPS
2004
14 years 11 months ago
Contextual Models for Object Detection Using Boosted Random Fields
We seek to both detect and segment objects in images. To exploit both local image data as well as contextual information, we introduce Boosted Random Fields (BRFs), which use boos...
Antonio Torralba, Kevin P. Murphy, William T. Free...
WS
2010
ACM
14 years 8 months ago
Structured literature image finder: Parsing text and figures in biomedical literature
The SLIF project combines text-mining and image processing to extract structured information from biomedical literature. SLIF extracts images and their captions from published pap...
Amr Ahmed, Andrew Arnold, Luís Pedro Coelho...
ICDM
2002
IEEE
105views Data Mining» more  ICDM 2002»
15 years 2 months ago
Empirical Comparison of Various Reinforcement Learning Strategies for Sequential Targeted Marketing
We empirically evaluate the performance of various reinforcement learning methods in applications to sequential targeted marketing. In particular, we propose and evaluate a progre...
Naoki Abe, Edwin P. D. Pednault, Haixun Wang, Bian...
SDM
2009
SIAM
235views Data Mining» more  SDM 2009»
15 years 6 months ago
Topic Cube: Topic Modeling for OLAP on Multidimensional Text Databases.
As the amount of textual information grows explosively in various kinds of business systems, it becomes more and more desirable to analyze both structured data records and unstruc...
ChengXiang Zhai, Duo Zhang, Jiawei Han
TVCG
2011
163views more  TVCG 2011»
14 years 4 months ago
Scan-Based Volume Animation Driven by Locally Adaptive Articulated Registrations
—This paper describes a complete system to create anatomically accurate example-based volume deformation and animation of articulated body regions, starting from multiple in vivo...
Taehyun Rhee, John P. Lewis, Ulrich Neumann, Krish...