In recent years, deep artificial neural networks (including recurrent ones) have won
numerous contests in pattern recognition and machine learning. This historical survey …

Recurrent neural networks (RNNs) with Long Short-Term memory cells currently hold the
best known results in unconstrained handwriting recognition. We show that their …

In this paper, we are interested in modeling complex activities that occur in a typical
household. We propose to use programs, ie, sequences of atomic actions and interactions …

Multidimensional long short-term memory recurrent neural networks achieve impressive
results for handwriting recognition. However, with current CPU-based implementations, their …

The recent advances in deep learning (DL) have caused breakthroughs in many fields such
as computer vision, natural language processing (NLP) and speech processing. Many DL …

Unconstrained text recognition is an important computer vision task, featuring a wide variety
of different sub-tasks, each with its own set of challenges. One of the biggest promises of …

We present initial results on the use of Multi-Dimensional Long-Short Term Memory
Recurrent Neural Networks (MDLSTM-RNN) in recognizing lines of handwritten Chinese …

The automatic transcription of text in handwritten documents has many applications, from
automatic document processing, to indexing and document understanding. One of the most …

Methods and systems are provided for end-to-end text recognition in digitized documents of
handwritten characters over multiple lines without explicit line segmentation. An image is …

Sequence-to-sequence models have recently become very popular for tackling handwritten
word recognition problems. However, how to effectively integrate an external language …