TY  - CONF
AU  - Juan Ignacio Toledo
AU  - Sebastian Sudholt
AU  - Alicia Fornes
AU  - Jordi Cucurull
AU  - A. Fink
AU  - Josep Llados
A2  - S+SSPR
PY  - 2016//
TI  - Handwritten Word Image Categorization with Convolutional Neural Networks and Spatial Pyramid Pooling
T2  - LNCS
BT  - Joint IAPR International Workshops on Statistical Techniques in Pattern Recognition (SPR) and Structural and Syntactic Pattern Recognition (SSPR)
SP  - 543
EP  - 552
VL  - 10029
PB  - Springer International Publishing
KW  - Document image analysis
KW  - Word image categorization
KW  - Convolutional neural networks
KW  - Named entity detection
N2  - The extraction of relevant information from historical document collections is one of the key steps in order to make these documents available for access and searches. The usual approach combines transcription and grammars in order to extract semantically meaningful entities. In this paper, we describe a new method to obtain word categories directly from non-preprocessed handwritten word images. The method can be used to directly extract information, being an alternative to the transcription. Thus it can be used as a first step in any kind of syntactical analysis. The approach is based on Convolutional Neural Networks with a Spatial Pyramid Pooling layer to deal with the different shapes of the input images. We performed the experiments on a historical marriage record dataset, obtaining promising results.
SN  - 978-3-319-49054-0
UR  - http://link.springer.com/chapter/10.1007/978-3-319-49055-7_48
L1  - http://refbase.cvc.uab.es/files/TSF2016.pdf
N1  - DAG; 600.097; 602.006
ID  - Juan Ignacio Toledo2016
ER  -