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ECCV
2010
Springer
13 years 9 months ago
MIForests: Multiple-Instance Learning with Randomized Trees
Abstract. Multiple-instance learning (MIL) allows for training classifiers from ambiguously labeled data. In computer vision, this learning paradigm has been recently used in many ...
Christian Leistner, Amir Saffari, Horst Bischof
CVIU
2007
174views more  CVIU 2007»
13 years 9 months ago
Laser-based detection and tracking of multiple people in crowds
Laser-based people tracking systems have been developed for mobile robotic, and intelligent surveillance areas. Existing systems rely on laser point clustering method to extract o...
Jinshi Cui, Hongbin Zha, Huijing Zhao, Ryosuke Shi...
APGV
2009
ACM
196views Visualization» more  APGV 2009»
14 years 3 months ago
Effects of animation, user-controlled interactions, and multiple static views in understanding 3D structures
Visualizations of 3D spatial structures use various techniques such as user controlled interactions or 2D projection views to convey the structure to users. Researchers have shown...
Taylor Sando, Melanie Tory, Pourang Irani
CVBIA
2005
Springer
14 years 2 months ago
Analyzing Anatomical Structures: Leveraging Multiple Sources of Knowledge
Analysis of medical images, especially the extraction of anatomical structures, is a critical component of many medical applications: surgical planning and navigation, and populati...
W. Eric L. Grimson, Polina Golland
BMCBI
2006
137views more  BMCBI 2006»
13 years 9 months ago
Sigma: multiple alignment of weakly-conserved non-coding DNA sequence
Background: Existing tools for multiple-sequence alignment focus on aligning protein sequence or protein-coding DNA sequence, and are often based on extensions to Needleman-Wunsch...
Rahul Siddharthan