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ICASSP
2011
IEEE
12 years 11 months ago
Deep Belief Networks using discriminative features for phone recognition
Deep Belief Networks (DBNs) are multi-layer generative models. They can be trained to model windows of coefficients extracted from speech and they discover multiple layers of fea...
Abdel-rahman Mohamed, Tara N. Sainath, George Dahl...
INTERSPEECH
2010
13 years 2 months ago
Hierarchical bottle neck features for LVCSR
This paper investigates the combination of different neural network topologies for probabilistic feature extraction. On one hand, a five-layer neural network used in bottle neck f...
Christian Plahl, Ralf Schlüter, Hermann Ney
ICMCS
2000
IEEE
116views Multimedia» more  ICMCS 2000»
13 years 11 months ago
Non-linear Relevance Feedback: Improving the Performance of Content-Based Retrieval Systems
In this paper, a non-linear relevance feedback mechanism is proposed for increasing the performance and the reliability of content-based retrieval systems. In particular, the huma...
Nikolaos D. Doulamis, Anastasios D. Doulamis, Stef...
IJON
2000
71views more  IJON 2000»
13 years 7 months ago
Variable selection using neural-network models
In this paper we propose an approach to variable selection that uses a neural-network model as the tool to determine which variables are to be discarded. The method performs a bac...
Giovanna Castellano, Anna Maria Fanelli
ESANN
2004
13 years 8 months ago
Face Recognition Using Recurrent High-Order Associative Memories
A novel face recognition approach is proposed, based on the use of compressed discriminative features and recurrent neural classifiers. Low-dimensional feature vectors are extract...
Iulian B. Ciocoiu