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	Author	Juan Ignacio Toledo; Sebastian Sudholt; Alicia Fornes; Jordi Cucurull; A. Fink; Josep Llados
	Title	Handwritten Word Image Categorization with Convolutional Neural Networks and Spatial Pyramid Pooling			Type	Conference Article
	Year	2016	Publication	Joint IAPR International Workshops on Statistical Techniques in Pattern Recognition (SPR) and Structural and Syntactic Pattern Recognition (SSPR)	Abbreviated Journal
	Volume	10029	Issue		Pages	543-552
	Keywords	Document image analysis; Word image categorization; Convolutional neural networks; Named entity detection
	Abstract	The extraction of relevant information from historical document collections is one of the key steps in order to make these documents available for access and searches.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.
	Address	Merida; Mexico; December 2016
	Corporate Author				Thesis
	Publisher	Springer International Publishing	Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title	LNCS
	Series Volume		Series Issue		Edition
	ISSN		ISBN	978-3-319-49054-0	Medium
	Area		Expedition		Conference	S+SSPR
	Notes	DAG; 600.097; 602.006			Approved	no
	Call Number	Admin @ si @ TSF2016			Serial	2877
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