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» Rule extraction from linear support vector machines
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CORR
2006
Springer
130views Education» more  CORR 2006»
15 years 1 months ago
Genetic Programming for Kernel-based Learning with Co-evolving Subsets Selection
Abstract. Support Vector Machines (SVMs) are well-established Machine Learning (ML) algorithms. They rely on the fact that i) linear learning can be formalized as a well-posed opti...
Christian Gagné, Marc Schoenauer, Mich&egra...
131
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AIME
2009
Springer
14 years 11 months ago
Segmentation of Lung Tumours in Positron Emission Tomography Scans: A Machine Learning Approach
Lung cancer represents the most deadly type of malignancy. In this work we propose a machine learning approach to segmenting lung tumours in Positron Emission Tomography (PET) scan...
Aliaksei Kerhet, Cormac Small, Harvey Quon, Terenc...
BMCBI
2008
124views more  BMCBI 2008»
15 years 2 months ago
Computational identification of ubiquitylation sites from protein sequences
Background: Ubiquitylation plays an important role in regulating protein functions. Recently, experimental methods were developed toward effective identification of ubiquitylation...
Chun-Wei Tung, Shinn-Ying Ho
MLDM
2005
Springer
15 years 7 months ago
Low-Level Cursive Word Representation Based on Geometric Decomposition
Abstract. An efficient low-level word image representation plays a crucial role in general cursive word recognition. This paper proposes a novel representation scheme, where a word...
Jian-xiong Dong, Adam Krzyzak, Ching Y. Suen, Domi...
ICIP
2005
IEEE
16 years 3 months ago
Eigenwalks: walk detection and biometrics from symmetry patterns
In this paper we present a symmetry-based approach which can be used to detect humans and to extract biometric characteristics from video image-sequences. The method employs a simp...
Laszlo Havasi, Tamás Szirányi, Zolt&...