9 citations · 9 across the 2 of their papers we have counts for
7 papers
Data Incubation -- Synthesizing Missing Data for Handwriting Recognition
Jen-Hao Rick Chang, Martin Bresler, Youssouf Chherawala +4
In this paper, we demonstrate how a generative model can be used to build a better recognizer through the control of content and style. We are building an online handwriting recogn…
CoSE: Compositional Stroke Embeddings
Emre Aksan, Thomas Deselaers, Andrea Tagliasacchi +1
We present a generative model for complex free-form structures such as stroke-based drawing tasks. While previous approaches rely on sequence-based models for drawings of basic obj…
The DIDI dataset: Digital Ink Diagram data
Philippe Gervais, Thomas Deselaers, Emre Aksan +1
We are releasing a dataset of diagram drawings with dynamic drawing information. The dataset aims to foster research in interactive graphical symbolic understanding. The dataset wa…
A Scalable Handwritten Text Recognition System
R. Reeve Ingle, Yasuhisa Fujii, Thomas Deselaers +2
Many studies on (Offline) Handwritten Text Recognition (HTR) systems have focused on building state-of-the-art models for line recognition on small corpora. However, adding HTR cap…
IndyLSTMs: Independently Recurrent LSTMs
Pedro Gonnet, Thomas Deselaers
We introduce Independently Recurrent Long Short-term Memory cells: IndyLSTMs. These differ from regular LSTM cells in that the recurrent weights are not modeled as a full matrix, b…
Fast Multi-language LSTM-based Online Handwriting Recognition
Victor Carbune, Pedro Gonnet, Thomas Deselaers +7
We describe an online handwriting system that is able to support 102 languages using a deep neural network architecture. This new system has completely replaced our previous Segmen…