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ECCV
2008
Springer
16 years 1 months ago
Training Hierarchical Feed-Forward Visual Recognition Models Using Transfer Learning from Pseudo-Tasks
Abstract. Building visual recognition models that adapt across different domains is a challenging task for computer vision. While feature-learning machines in the form of hierarchi...
Amr Ahmed, Kai Yu, Wei Xu, Yihong Gong, Eric P. Xi...
ICDAR
2009
IEEE
15 years 6 months ago
Evaluating Retraining Rules for Semi-Supervised Learning in Neural Network Based Cursive Word Recognition
Training a system to recognize handwritten words is a task that requires a large amount of data with their correct transcription. However, the creation of such a training set, inc...
Volkmar Frinken, Horst Bunke
AIA
2007
15 years 1 months ago
Optimizing number of hidden neurons in neural networks
In this paper, a novel and effective criterion based on the estimation of the signal-to-noise-ratio figure (SNRF) is proposed to optimize the number of hidden neurons in neural ne...
Yue Liu, Janusz A. Starzyk, Zhen Zhu
RAID
1999
Springer
15 years 4 months ago
Improving Intrusion Detection Performance using Keyword Selection and Neural Networks
The most common computer intrusion detection systems detect signatures of known attacks by searching for attack-specific keywords in network traffic. Many of these systems suffer ...
Richard Lippmann, Robert K. Cunningham
ICASSP
2011
IEEE
14 years 3 months ago
Arccosine kernels: Acoustic modeling with infinite neural networks
Neural networks are a useful alternative to Gaussian mixture models for acoustic modeling; however, training multilayer networks involves a difficult, nonconvex optimization that...
Chih-Chieh Cheng, Brian Kingsbury