M
Masaki Nakagawa
Researcher at Tokyo University of Agriculture and Technology
Publications - 268
Citations - 3220
Masaki Nakagawa is an academic researcher from Tokyo University of Agriculture and Technology. The author has contributed to research in topics: Handwriting recognition & Intelligent word recognition. The author has an hindex of 26, co-authored 268 publications receiving 2900 citations. Previous affiliations of Masaki Nakagawa include University at Buffalo & University of Tokyo.
Papers
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'Online recognition of Chinese characters: the state-of-the-art
TL;DR: This paper reviews the advances in online Chinese character recognition (OLCCR), with emphasis on the research works from the 1990s, in terms of pattern representation, character classification, learning/adaptation, and contextual processing.
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Evaluation of prototype learning algorithms for nearest-neighbor classifier in application to handwritten character recognition
Cheng-Lin Liu,Masaki Nakagawa +1 more
TL;DR: In this paper, prototype learning is used to improve the classification performance of nearest-neighbor (NN) classifier and reduce the storage and computation requirements of NN classifier.
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Collection of on-line handwritten Japanese character pattern databases and their analyses
Masaki Nakagawa,Kaoru Matsumoto +1 more
TL;DR: The design of on-line handwritten Japanese character pattern databases, software tools for pattern collection and verification, and analyses of collected patterns reveal greater variations in stroke count for characters having many strokes, with people generally using fewer strokes.
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Handwritten Chinese/Japanese Text Recognition Using Semi-Markov Conditional Random Fields
TL;DR: A forward-backward lattice pruning algorithm is proposed to reduce the computation in training when trigram language models are used, and beam search techniques are investigated to accelerate the decoding speed.
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The state of the art in Japanese online handwriting recognition compared to techniques in western handwriting recognition
TL;DR: This paper compares the current state of the art in online Japanese character recognition with techniques in western handwriting recognition to help develop compact modules for integrated systems supporting many writing systems capable of recognizing multilanguage documents.