Improving Japanese semantic-role-labeling performance with transfer learning as case for limited resources of tagged corpora on aggregated language

no code implementations • PACLIC 2018 • Takuya Okamura, Koichi Takeuchi, Yasuhiro Ishihara, Masahiro Taguchi, Yoshihiko Inada, Masaya Iizuka, Tatsuhiko Abo, Hitoshi Ueda

Semantic Role Labeling Transfer Learning

Tips and Tricks to Improve CNN-based Chest X-ray Diagnosis: A Survey

no code implementations • 2 Jun 2021 • Changhee Han, Takayuki Okamoto, Koichi Takeuchi, Dimitris Katsios, Andrey Grushnikov, Masaaki Kobayashi, Antoine Choppin, Yutaka Kurashina, Yuki Shimahara

Convolutional Neural Networks (CNNs) intrinsically requires large-scale data whereas Chest X-Ray (CXR) images tend to be data/annotation-scarce, leading to over-fitting.

Specificity

Constructing Web-Accessible Semantic Role Labels and Frames for Japanese as Additions to the NPCMJ Parsed Corpus

no code implementations • LREC 2020 • Koichi Takeuchi, Alastair Butler, Iku Nagasaki, Takuya Okamura, Prashant Pardeshi

As part of constructing the NINJAL Parsed Corpus of Modern Japanese (NPCMJ), a web-accessible language resource, we are adding frame information for predicates, together with two types of semantic role labels that mark the contributions of arguments.

AMR Parsing

A Method of Augmenting Bilingual Terminology by Taking Advantage of the Conceptual Systematicity of Terminologies

no code implementations • WS 2016 • Miki Iwai, Koichi Takeuchi, Kyo Kageura, Kazuya Ishibashi

In this paper, we propose a method of augmenting existing bilingual terminologies.

Transfer Learning