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ICDAR
2003
IEEE
16 years 3 days ago
Best Practices for Convolutional Neural Networks Applied to Visual Document Analysis
Neural networks are a powerful technology for classification of visual inputs arising from documents. However, there is a confusing plethora of different neural network methods th...
Patrice Simard, David Steinkraus, John C. Platt
NEUROSCIENCE
2001
Springer
15 years 11 months ago
Finite-State Computation in Analog Neural Networks: Steps towards Biologically Plausible Models?
Abstract. Finite-state machines are the most pervasive models of computation, not only in theoretical computer science, but also in all of its applications to real-life problems, a...
Mikel L. Forcada, Rafael C. Carrasco
CORR
2010
Springer
116views Education» more  CORR 2010»
15 years 1 months ago
Mixed-Membership Stochastic Block-Models for Transactional Networks
Abstract: Transactional network data can be thought of as a list of oneto-many communications (e.g., email) between nodes in a social network. Most social network models convert th...
Mahdi Shafiei, Hugh Chipman
ICASSP
2009
IEEE
16 years 1 months ago
Robust discriminative keyword spotting for emotionally colored spontaneous speech using bidirectional LSTM networks
In this paper we propose a new technique for robust keyword spotting that uses bidirectional Long Short-Term Memory (BLSTM) recurrent neural nets to incorporate contextual informa...
Martin Wöllmer, Florian Eyben, Joseph Keshet,...
ICDAR
2009
IEEE
16 years 1 months ago
Graphic Symbol Recognition Using Graph Based Signature and Bayesian Network Classifier
We present a new approach for recognition of complex graphic symbols in technical documents. Graphic symbol recognition is a well known challenge in the field of document image an...
Muhammad Muzzamil Luqman, Thierry Brouard, Jean-Yv...