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IJCNN
2006
IEEE
13 years 10 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...
BMCBI
2005
251views more  BMCBI 2005»
13 years 4 months ago
Contextual weighting for Support Vector Machines in literature mining: an application to gene versus protein name disambiguation
Background: The ability to distinguish between genes and proteins is essential for understanding biological text. Support Vector Machines (SVMs) have been proven to be very effici...
Tapio Pahikkala, Filip Ginter, Jorma Boberg, Jouni...
RTAS
2003
IEEE
13 years 9 months ago
Collaborative Operating System and Compiler Power Management for Real-Time Applications
Managing energy consumption has become vitally important to battery operated portable and embedded systems. A dynamic voltage scaling (DVS) technique reduces the processor’s dyn...
Nevine AbouGhazaleh, Daniel Mossé, Bruce R....
ICCV
2009
IEEE
14 years 9 months ago
Learning Deformable Action Templates from Crowded Videos
In this paper, we present a Deformable Action Template (DAT) model that is learnable from cluttered real-world videos with weak supervisions. In our generative model, an action ...
Benjamin Yao, Song-Chun Zhu