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IJCNN
2006
IEEE
14 years 1 months ago
Adaptation of Artificial Neural Networks Avoiding Catastrophic Forgetting
— In connectionist learning, one relevant problem is “catastrophic forgetting” that may occur when a network, trained with a large set of patterns, has to learn new input pat...
Dario Albesano, Roberto Gemello, Pietro Laface, Fr...
AAAI
2010
13 years 4 months ago
Multilinear Maximum Distance Embedding Via L1-Norm Optimization
Dimensionality reduction plays an important role in many machine learning and pattern recognition tasks. In this paper, we present a novel dimensionality reduction algorithm calle...
Yang Liu, Yan Liu, Keith C. C. Chan
ISCAS
2003
IEEE
108views Hardware» more  ISCAS 2003»
14 years 1 months ago
Usable speech measures and their fusion
Usable speech is a novel concept related to the co-channel speech problem. Co-channel speech occurs when more than one person is talking at the same time. The idea of usable speec...
Robert E. Yantorno, Brett Y. Smolenski
MVA
2007
210views Computer Vision» more  MVA 2007»
13 years 9 months ago
Represent Image Contents Using Curves and Chain Code
This paper presents a new approach to extracting and representing structural features of images. The approach is based on both a region-based analysis and a contour-based analysis...
Pornchai Mongkolnam, Chakarida Nukoolkit, Thanee D...
SIGMOD
2003
ACM
237views Database» more  SIGMOD 2003»
14 years 8 months ago
Qcluster: Relevance Feedback Using Adaptive Clustering for Content-Based Image Retrieval
The learning-enhanced relevance feedback has been one of the most active research areas in content-based image retrieval in recent years. However, few methods using the relevance ...
Deok-Hwan Kim, Chin-Wan Chung