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CVPR
2007
IEEE
14 years 9 months ago
Detection and segmentation of moving objects in highly dynamic scenes
Detecting and segmenting moving objects in dynamic scenes is a hard but essential task in a number of applications such as surveillance. Most existing methods only give good resul...
Aurélie Bugeau, Patrick Pérez
BMCBI
2006
144views more  BMCBI 2006»
13 years 7 months ago
More robust detection of motifs in coexpressed genes by using phylogenetic information
Background: Several motif detection algorithms have been developed to discover overrepresented motifs in sets of coexpressed genes. However, in a noisy gene list, the number of ge...
Pieter Monsieurs, Gert Thijs, Abeer A. Fadda, Sigr...
GECCO
2008
Springer
162views Optimization» more  GECCO 2008»
13 years 8 months ago
Robust method of detecting moving objects in videos evolved by genetic programming
In this paper we investigated the use of Genetic Programming (GP) to evolve programs which could detect moving objects in videos. Two main approaches under the paradigm were propo...
Andy Song, Danny Fang
BMCBI
2010
171views more  BMCBI 2010»
13 years 7 months ago
PyMix - The Python mixture package - a tool for clustering of heterogeneous biological data
Background: Cluster analysis is an important technique for the exploratory analysis of biological data. Such data is often high-dimensional, inherently noisy and contains outliers...
Benjamin Georgi, Ivan Gesteira Costa, Alexander Sc...
FGR
2008
IEEE
208views Biometrics» more  FGR 2008»
14 years 1 months ago
Unsupervised learning from local features for video-based face recognition
This paper presents an unsupervised learning approach to video-based face recognition that does not make any assumptions about the pose, expressions or prior localization of landm...
Ajmal Mian