activity
20182021
most citedA large-scale field test on word-image classification in large historical document collections using a traditional and two deep-learning methods

1 citations · 1 across the 2 of their papers we have counts for

collaborators

5 papers

cs.CL2021

Active learning for reducing labeling effort in text classification tasks

Pieter Floris Jacobs, Gideon Maillette de Buy Wenniger, Marco Wiering +1

Labeling data can be an expensive task as it is usually performed manually by domain experts. This is cumbersome for deep learning, as it is dependent on large labeled datasets. Ac…

cs.CV20191 cited

A large-scale field test on word-image classification in large historical document collections using a traditional and two deep-learning methods

Lambert Schomaker

This technical report describes a practical field test on word-image classification in a very large collection of more than 300 diverse handwritten historical manuscripts, with 1.6…

cs.CV2019

No Padding Please: Efficient Neural Handwriting Recognition

Gideon Maillette de Buy Wenniger, Lambert Schomaker, Andy Way

Neural handwriting recognition (NHR) is the recognition of handwritten text with deep learning models, such as multi-dimensional long short-term memory (MDLSTM) recurrent neural ne…

cs.CV2018

Deep Adaptive Learning for Writer Identification based on Single Handwritten Word Images

Sheng He, Lambert Schomaker

There are two types of information in each handwritten word image: explicit information which can be easily read or derived directly, such as lexical content or word length, and im…

cs.CV2018

Open Set Chinese Character Recognition using Multi-typed Attributes

Sheng He, Lambert Schomaker

Recognition of Off-line Chinese characters is still a challenging problem, especially in historical documents, not only in the number of classes extremely large in comparison to co…