@article{oai:ous.repo.nii.ac.jp:00001120,
 author = {大倉, 充 and Ohkura, Mitsuru and 塩野, 充 and Shiono, Mitsuru and 橋本, 禮治 and Hashimoto, Reiji},
 journal = {岡山理科大学紀要. A, 自然科学, Bulletin of Okayama University of Science. A, Natural Sciences},
 month = {Mar},
 note = {P(論文), Handwritten HIRAGANA characters are classified according to whether they have DAKUTEN (or HAN-DAKUTEN) or not by the 3-layer neural networks. The input data to the networks is 25-dimensional local mesh-feature extracted from an original character pattern. The numbers of units of three layers are 25 (input-layer), 25 (hidden-layer) and 2 (output-layer). The numbers of training and unknown samples used in a classification experiment are 6900 and 5000,respectively. The average classification rate of 94(%) for the unknown samples is obtained.},
 pages = {319--327},
 title = {ニューラルネットワークを用いた濁点,半濁点の有無による手書き平仮名の分類},
 volume = {30},
 year = {1995},
 yomi = {オオクラ, ミツル and シオノ, ミツル and ハシモト, レイジ}
}