Fast and accurate candidate reduction using the multiclass LDA for Japanese/Chinese character recognition. - Ryosuke Odate; Hideaki Goto (ICIP, 2015)

Highly-accurate fast candidate reduction method for Japanese/Chinese character recognition. - Ryosuke Odate; Hideaki Goto (ICIP, 2016)

Semi-supervised Clustering Framework Based on Active Learning for Real Data. - Ryosuke Odate; Hiroshi Shinjo; Yasufumi Suzuki; Masahiro Motobayashi (S+SSPR, 2018)

Automatic Annotation Method for Document Image Binarization in Real Systems. - Ryosuke Odate (ACPR (2), 2019)

A High Accuracy Text Detection Model of Newly Constructing and Training Strategies. - Kha Cong Nguyen; Ryosuke Odate (ICPRAM, 2021)

Incremental Teacher Model with Mixed Augmentations and Scheduled Pseudo-label Loss for Handwritten Text Recognition. - Masayuki Honda; Hung Tuan Nguyen; Cuong Tuan Nguyen; Kha Cong Nguyen; Ryosuke Odate; Takashi Kanemaru; Masaki Nakagawa (ICDAR (4), 2023)