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EPS
1998
Springer
13 years 11 months ago
Genetic Programming for Automatic Target Classification and Recognition
We use the genetic programming (GP) paradigm for two tasks. The first task given a GP is the generation of rules for the target / clutter classification of a set of synthetic apert...
Stephen A. Stanhope, Jason M. Daida
BMCBI
2004
131views more  BMCBI 2004»
13 years 6 months ago
Detection of chromosomal regions showing differential gene expression in human skeletal muscle and in alveolar rhabdomyosarcoma
Background: Rhabdomyosarcoma is a relatively common tumour of the soft tissue, probably due to regulatory disruption of growth and differentiation of skeletal muscle stem cells. I...
Andrea Bisognin, Stefania Bortoluzzi, Gian Antonio...
IJCV
2008
192views more  IJCV 2008»
13 years 6 months ago
Learning to Locate Informative Features for Visual Identification
Object identification (OID) is specialized recognition where the category is known (e.g. cars) and the algorithm recognizes an object's exact identity (e.g. Bob's BMW). ...
Andras Ferencz, Erik G. Learned-Miller, Jitendra M...
BMCBI
2006
216views more  BMCBI 2006»
13 years 6 months ago
Machine learning approaches to supporting the identification of photoreceptor-enriched genes based on expression data
Background: Retinal photoreceptors are highly specialised cells, which detect light and are central to mammalian vision. Many retinal diseases occur as a result of inherited dysfu...
Haiying Wang, Huiru Zheng, David Simpson, Francisc...
CORR
2010
Springer
104views Education» more  CORR 2010»
13 years 6 months ago
Offline Signature Identification by Fusion of Multiple Classifiers using Statistical Learning Theory
This paper uses Support Vector Machines (SVM) to fuse multiple classifiers for an offline signature system. From the signature images, global and local features are extracted and ...
Dakshina Ranjan Kisku, Phalguni Gupta, Jamuna Kant...