An end-to-end pipeline for historical censuses processing
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Text characters embedded in images and video sequences represents a rich source of information for content-based indexing and retrieval applications. However, these text characters are difficult to be detected and recognized due to their various sizes, gra ...
Text characters embedded in images and video sequences represents a rich source of information for content-based indexing and retrieval applications. However, these text characters are difficult to be detected and recognized due to their various sizes, gra ...
This paper completes the study presented in the accompanying paper, and demonstrates a numerical algorithm for parameter prediction from the piezocone test (CPTU) data. This part deals with a development of neural network (NN) models which are able to map ...
Text characters embedded in images and video sequences represents a rich source of information for content-based indexing and retrieval applications. However, these text characters are difficult to be detected and recognized due to their various sizes, gra ...
This paper introduces Graph Convolutional Recurrent Network (GCRN), a deep learning model able to predict structured sequences of data. Precisely, GCRN is a generalization of classical recurrent neural networks (RNN) to data structured by an arbitrary grap ...
Text embedded in images and videos represents a rich source of information for content-based indexing and retrieval applications. In this paper, we present a new method for localizing and recognizing text in complex images and videos. Text localization is ...
A Language Model (LM) is a helpful component of a variety of Natural Language Processing (NLP) systems today. For speech recognition, machine translation, information retrieval, word sense disambiguation etc., the contribution of an LM is to provide featur ...
This paper investigates the use of a hierarchy of Neural Networks for performing data driven feature extraction. Two different hierarchical structures based on long and short temporal context are considered. Features are tested on two different LVCSR syste ...
IDIAP2007
For a long time, natural language processing (NLP) has relied on generative models with task specific and manually engineered features. Recently, there has been a resurgence of interest for neural networks in the machine learning community, obtaining state ...
EPFL2016
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This paper investigates the use of a hierarchy of Neural Networks for performing data driven feature extraction. Two different hierarchical structures based on long and short temporal context are considered. Features are tested on two different LVCSR syste ...
