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» The importance of learning in fuzzy systems
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ICONIP
1998
13 years 9 months ago
ECOS: Evolving Connectionist Systems and the ECO Learning Paradigm
The paper presents a framework called ECOS for Evolving COnnectionist Systems. ECOS evolve through incremental learning. They can accommodate any new input data, including new fea...
Nikola K. Kasabov
HICSS
2008
IEEE
105views Biometrics» more  HICSS 2008»
14 years 2 months ago
Video Content Description Using Fuzzy Spatio-temporal Relations
One of the important aspects in digital video applications is spatial and temporal characteristic. A very little progress has been achieved on spatiotemporal modeling of video dat...
Archana M. Rajurkar, R. C. Joshi, Santanu Chaudhar...
CORR
2004
Springer
208views Education» more  CORR 2004»
13 years 7 months ago
Business Intelligence from Web Usage Mining
The rapid e-commerce growth has made both business community and customers face a new situation. Due to intense competition on the one hand and the customer's option to choose...
Ajith Abraham
WILF
2009
Springer
196views Fuzzy Logic» more  WILF 2009»
14 years 2 days ago
Interactive Image Retrieval in a Fuzzy Framework
In this paper, an interactive image retrieval scheme using MPEG-7 visual descriptors is proposed. The performance of image retrieval systems is still limited due to semantic gap, w...
Malay Kumar Kundu, Minakshi Banerjee, Priyank Bagr...
BMCBI
2007
207views more  BMCBI 2007»
13 years 7 months ago
Discovering biomarkers from gene expression data for predicting cancer subgroups using neural networks and relational fuzzy clus
Background: The four heterogeneous childhood cancers, neuroblastoma, non-Hodgkin lymphoma, rhabdomyosarcoma, and Ewing sarcoma present a similar histology of small round blue cell...
Nikhil R. Pal, Kripamoy Aguan, Animesh Sharma, Shu...