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» On speaker adaptive training of artificial neural networks
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CVPR
2012
IEEE
13 years 3 days ago
Image denoising: Can plain neural networks compete with BM3D?
Image denoising can be described as the problem of mapping from a noisy image to a noise-free image. The best currently available denoising methods approximate this mapping with c...
Harold Christopher Burger, Christian J. Schuler, S...
53
Voted
WCE
2007
14 years 10 months ago
E-learning System Based on Neural Networks
—Although the current E-Learning systems have many merits, many of them only treat advanced information technology as simple communication tools, and release some learning conten...
Linfeng Zhang, Fei Yu, Yue Shen, Guiping Liao, Ken...
PAKDD
2000
ACM
161views Data Mining» more  PAKDD 2000»
15 years 1 months ago
Adaptive Boosting for Spatial Functions with Unstable Driving Attributes
Combining multiple global models (e.g. back-propagation based neural networks) is an effective technique for improving classification accuracy by reducing a variance through manipu...
Aleksandar Lazarevic, Tim Fiez, Zoran Obradovic
IJCNN
2008
IEEE
15 years 4 months ago
Learning adaptive subject-independent P300 models for EEG-based brain-computer interfaces
Abstract— This paper proposes an approach to learn subjectindependent P300 models for EEG-based brain-computer interfaces. The P300 models are first learned using a pool of exis...
Shijian Lu, Cuntai Guan, Haihong Zhang
ECAL
2005
Springer
15 years 3 months ago
Analysing the Evolvability of Neural Network Agents Through Structural Mutations
This paper investigates evolvability of artificial neural networks within an artificial life environment. Five different structural mutations are investigated, including adaptive e...
Ehud Schlessinger, Peter J. Bentley, R. Beau Lotto