Matches in SemOpenAlex for { <https://semopenalex.org/work/W2013114490> ?p ?o ?g. }
Showing items 1 to 67 of
67
with 100 items per page.
- W2013114490 endingPage "167" @default.
- W2013114490 startingPage "159" @default.
- W2013114490 abstract "In spite of the fact that subspace method can approximate the distribution of categories precisely, only a few attempts have so far been made at applying it in hand-written character recognition. The subspace method proposed by Watanabe (1969) offers the basic concept of subspace construction, but the issue of how to use the limited samples to construct effective subspace to avoid the problem of mis-recognition caused by the fact that the subspace of a category is almost parallel to the mean vector of the category remains unresolved. This problem leads to the mis-recognition of the samples far from the mean vector. To cope with this problem, Abe, Nemoto and Sun (1995) have proposed the Combination method (CM), which constructs the subspace from several groups including different number of samples divided from the whole training samples. CM obtained a high recognition rate of 97.76% with respect to ETL9B, the largest database of hand-written characters in Japan. ETL9B was published by Electro-technical Laboratory of Japan in 1985. It includes 2,965 categories of Chinese characters and 71 categories of Japanese Kana, there are 200 data sets in the database where each set has one sample per category. Total number of samples is 607,200. The issues that need to be dealt with next are how to improve the recognition accuracy and how to accelerate the recognition speed. In this paper, we propose a new method called Uniform Division Method (UDM), which uses the uniformly divided training samples to construct subspace. Compared to CM given earlier, UDM is very simple and effective enough to improve the accuracy of recognition; as a result, we obtained a recognition rate of 98.64% for ETL9B compared to the 97.76% for CM. This is the first time that such a high recognition rate has been obtained by making good use of subspace method. Furthermore, the computation required for UDM is less than a half of that of CM. The UDM algorithm and the experiments with ETL9B will be described in this paper." @default.
- W2013114490 created "2016-06-24" @default.
- W2013114490 creator A5013311265 @default.
- W2013114490 creator A5071040867 @default.
- W2013114490 date "1996-01-01" @default.
- W2013114490 modified "2023-09-27" @default.
- W2013114490 title "Hand-written Character Recognition System Using Uniform Division of Training Samples on Subspace Method." @default.
- W2013114490 doi "https://doi.org/10.4036/iis.1996.159" @default.
- W2013114490 hasPublicationYear "1996" @default.
- W2013114490 type Work @default.
- W2013114490 sameAs 2013114490 @default.
- W2013114490 citedByCount "0" @default.
- W2013114490 crossrefType "journal-article" @default.
- W2013114490 hasAuthorship W2013114490A5013311265 @default.
- W2013114490 hasAuthorship W2013114490A5071040867 @default.
- W2013114490 hasBestOaLocation W20131144901 @default.
- W2013114490 hasConcept C153180895 @default.
- W2013114490 hasConcept C153294291 @default.
- W2013114490 hasConcept C154945302 @default.
- W2013114490 hasConcept C204321447 @default.
- W2013114490 hasConcept C205649164 @default.
- W2013114490 hasConcept C2524010 @default.
- W2013114490 hasConcept C2777211547 @default.
- W2013114490 hasConcept C2780861071 @default.
- W2013114490 hasConcept C28490314 @default.
- W2013114490 hasConcept C2987247673 @default.
- W2013114490 hasConcept C32834561 @default.
- W2013114490 hasConcept C33923547 @default.
- W2013114490 hasConcept C41008148 @default.
- W2013114490 hasConcept C60798267 @default.
- W2013114490 hasConcept C94375191 @default.
- W2013114490 hasConceptScore W2013114490C153180895 @default.
- W2013114490 hasConceptScore W2013114490C153294291 @default.
- W2013114490 hasConceptScore W2013114490C154945302 @default.
- W2013114490 hasConceptScore W2013114490C204321447 @default.
- W2013114490 hasConceptScore W2013114490C205649164 @default.
- W2013114490 hasConceptScore W2013114490C2524010 @default.
- W2013114490 hasConceptScore W2013114490C2777211547 @default.
- W2013114490 hasConceptScore W2013114490C2780861071 @default.
- W2013114490 hasConceptScore W2013114490C28490314 @default.
- W2013114490 hasConceptScore W2013114490C2987247673 @default.
- W2013114490 hasConceptScore W2013114490C32834561 @default.
- W2013114490 hasConceptScore W2013114490C33923547 @default.
- W2013114490 hasConceptScore W2013114490C41008148 @default.
- W2013114490 hasConceptScore W2013114490C60798267 @default.
- W2013114490 hasConceptScore W2013114490C94375191 @default.
- W2013114490 hasIssue "2" @default.
- W2013114490 hasLocation W20131144901 @default.
- W2013114490 hasOpenAccess W2013114490 @default.
- W2013114490 hasPrimaryLocation W20131144901 @default.
- W2013114490 hasRelatedWork W1514458971 @default.
- W2013114490 hasRelatedWork W1998938004 @default.
- W2013114490 hasRelatedWork W2016349419 @default.
- W2013114490 hasRelatedWork W2042327336 @default.
- W2013114490 hasRelatedWork W2159633528 @default.
- W2013114490 hasRelatedWork W2160069326 @default.
- W2013114490 hasRelatedWork W2317343029 @default.
- W2013114490 hasRelatedWork W2321141263 @default.
- W2013114490 hasRelatedWork W2543161807 @default.
- W2013114490 hasRelatedWork W2164844972 @default.
- W2013114490 hasVolume "2" @default.
- W2013114490 isParatext "false" @default.
- W2013114490 isRetracted "false" @default.
- W2013114490 magId "2013114490" @default.
- W2013114490 workType "article" @default.