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IJCNN
2006
IEEE
15 years 10 months ago
Alleviating Catastrophic Forgetting via Multi-Objective Learning
— Handling catastrophic forgetting is an interesting and challenging topic in modeling the memory mechanisms of the human brain using machine learning models. From a more general...
Yaochu Jin, Bernhard Sendhoff
136
Voted
BMCBI
2006
216views more  BMCBI 2006»
15 years 4 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...
ICPR
2004
IEEE
16 years 5 months ago
Corner Detection Using Support Vector Machines
A support vector machine based algorithm for corner detection is presented. It is based on computing the direction of maximum gray-level change for each edge pixel in an image, an...
Malay K. Kundu, Minakshi Banerjee, Pabitra Mitra
ICPR
2006
IEEE
16 years 5 months ago
On Kernel Selection in Relevance Vector Machines Using Stability Principle
In this paper we propose an alternative interpretation of Bayesian learning based on maximal evidence principle. We establish a notion of local evidence which can be viewed as a c...
Dmitry Kropotov, Nikita Ptashko, Oleg Vasiliev, Dm...
ICPR
2004
IEEE
16 years 5 months ago
Signal Discrimination Using a Support Vector Machine for Genetic Syndrome Diagnosis
In this study, a support vector machine (SVM) classifies real world data of cytogenetic signals measured from fluorescence in-situ hybridization (FISH) images in order to diagnose...
Amit David, Boaz Lerner