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24 March 2014 Two-stage approach to keyword spotting in handwritten documents
Mehdi Haji, Mohammad R. Ameri, Tien D. Bui, Ching Y. Suen, Dominique Ponson
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Proceedings Volume 9021, Document Recognition and Retrieval XXI; 90210P (2014) https://doi.org/10.1117/12.2042265
Event: IS&T/SPIE Electronic Imaging, 2014, San Francisco, California, United States
Abstract
Separation of keywords from non-keywords is the main problem in keyword spotting systems which has traditionally been approached by simplistic methods, such as thresholding of recognition scores. In this paper, we analyze this problem from a machine learning perspective, and we study several standard machine learning algorithms specifically in the context of non-keyword rejection. We propose a two-stage approach to keyword spotting and provide a theoretical analysis of the performance of the system which gives insights on how to design the classifier in order to maximize the overall performance in terms of F-measure.
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Mehdi Haji, Mohammad R. Ameri, Tien D. Bui, Ching Y. Suen, and Dominique Ponson "Two-stage approach to keyword spotting in handwritten documents", Proc. SPIE 9021, Document Recognition and Retrieval XXI, 90210P (24 March 2014); https://doi.org/10.1117/12.2042265
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KEYWORDS
Binary data
Detection and tracking algorithms
Image segmentation
Machine learning
Feature extraction
Transform theory
Image classification
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