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ECCV
2010
Springer
13 years 10 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 10 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...
BMCBI
2006
137views more  BMCBI 2006»
13 years 10 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
GPCE
2007
Springer
14 years 4 months ago
Open multi-methods for c++
Multiple dispatch – the selection of a function to be invoked based on the dynamic type of two or more arguments – is a solution to several classical problems in object-orient...
Peter Pirkelbauer, Yuriy Solodkyy, Bjarne Stroustr...
TPDS
2010
118views more  TPDS 2010»
13 years 8 months ago
Using Parallel Bloom Filters for Multiattribute Representation on Network Services
—One widely used mechanism for representing membership of a set of items is the simple space-efficient randomized data structure known as Bloom filters. Yet, Bloom filters are no...
Bin Xiao, Yu Hua