@inproceedings{oai:ipsj.ixsq.nii.ac.jp:00192436,
 author = {Tarin, Clanuwat and Alex, Lamb and Asanobu, Kitamoto and Tarin, Clanuwat and Alex, Lamb and Asanobu, Kitamoto},
 book = {じんもんこん2018論文集},
 month = {Nov},
 note = {Kuzushiji has been used as a cursive writing style in Japan for over a thousand years. However, following the reform of Japanese language textbooks in the year 1900, Kuzushiji was no longer taught in schools. Thus at present, nearly all Japanese natives cannot read books written or published before 150 years ago. As a result, many important pieces of Japanese history are only accessible to a handful of specially trained scholars. This has motivated the use of machine learning to read Kuzushiji. To accomplish this, we propose a new way of using the U-Net architecture from Deep Learning to spot characters in manuscripts. For other researchers to use our system to search for characters or words in manuscripts written with Kuzushiji, only an image of the page of text needs to be given to our system as input. Other Kuzushiji word spotting method have limitations in characters or words written in different Jibos (字母) or root characters in Hentaigana (or variant Kana). Our proposed U-Net character spotting system not only gives results with state-of-the- art accuracy, our system also resolves the Jibo problem, allowing our system to search for input characters in the text. While we present results for character spotting, we discuss keyword search as an exciting area for future work., Kuzushiji has been used as a cursive writing style in Japan for over a thousand years. However, following the reform of Japanese language textbooks in the year 1900, Kuzushiji was no longer taught in schools. Thus at present, nearly all Japanese natives cannot read books written or published before 150 years ago. As a result, many important pieces of Japanese history are only accessible to a handful of specially trained scholars. This has motivated the use of machine learning to read Kuzushiji. To accomplish this, we propose a new way of using the U-Net architecture from Deep Learning to spot characters in manuscripts. For other researchers to use our system to search for characters or words in manuscripts written with Kuzushiji, only an image of the page of text needs to be given to our system as input. Other Kuzushiji word spotting method have limitations in characters or words written in different Jibos (字母) or root characters in Hentaigana (or variant Kana). Our proposed U-Net character spotting system not only gives results with state-of-the- art accuracy, our system also resolves the Jibo problem, allowing our system to search for input characters in the text. While we present results for character spotting, we discuss keyword search as an exciting area for future work.},
 pages = {15--20},
 publisher = {情報処理学会},
 title = {End-to-End Pre-Modern Japanese Character (Kuzushiji) Spotting with Deep Learning},
 volume = {2018},
 year = {2018}
}