Published Papers - Yamada Koji

Intelligent Eye-Controlled Electric Wheelchair Based on Estimating Visual Intentions Using One-Dimensional Convolutional Neural Network and Long Short-Term Memory.

Higa S, Yamada K, Kamisato S

Sensors (Basel, Switzerland) ( Sensors )  23 ( 8 )   2023.04 [ Peer Review Accepted ]

Type of publication: Research paper (scientific journal)

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Gaze Analysis of Gaze Input Type Electric Wheelchair Passenger Using VR Simulator

YAMAMOTO Shoki, HIGA Sho, YAMADA Koji, KAMISATO Shihoko

The Proceedings of JSME annual Conference on Robotics and Mechatronics (Robomec) ( The Japan Society of Mechanical Engineers )  2023 ( 0 ) 2A1-F20   2023

Type of publication: Research paper (scientific journal)

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<p>Recently, there have been attempts to use eye gaze as an interface for electric wheelchairs. In this study, we develop a VR simulator for a gaze-input type electric wheelchair and measure gaze data to analyze gaze behavior during electric wheelchair operation.</p>

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Development of an Intention Estimation Model Based on Gaze and Face Information for Electric Wheelchair Operation Support

Higa Sho, Yamada Koji, Kamisato Shihoko

IEEJ Transactions on Electronics, Information and Systems ( The Institute of Electrical Engineers of Japan )  142 ( 4 ) 491 - 498   2022.04 [ Peer Review Accepted ]

Type of publication: Research paper (scientific journal)

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<p>In recent years, various user interfaces have been developed to meet the diverse needs of physically disabled persons. In this paper, we developed a method to identify gazing and facial movements based on gaze time and eye/face information and developed an electric wheelchair that can be operated with the user's "natural gazing and facial movements. This intention estimation model is composed of 1DCNN and LSTM layers. First, 1DCNN is used to extract features from gaze and face information, and then the extracted features are input to LSTM to estimate the user's intentions regarding movement. The evaluation experiments suggest that the combination of gaze and face information improves the estimation accuracy and contributes to the classification. Furthermore, it was confirmed that adding a convolutional filter layer to the LSTM layer improved the accuracy.</p>

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Development of the Estimation Model for Intentions to Move Based on Gaze and Face Information with 1DCNN-LSTM and Evaluation of Electric Wheelchair Driving

Sho Higa, Koji Yamada, Shihoko Kamisato

2021 Ninth International Symposium on Computing and Networking Workshops (CANDARW) ( IEEE )    429 - 433   2021.11 [ Peer Review Accepted ]

Type of publication: Research paper (international conference proceedings)

MolGANの拡張による文章グラフを用いた文章生成手法の提案

澤崎 夏希, 遠藤 聡志, 當間 愛晃, 山田 孝治, 赤嶺 有平

知能と情報 ( 日本知能情報ファジィ学会 )  32 ( 2 ) 668 - 677   2020 [ Peer Review Accepted ]

Type of publication: Research paper (scientific journal)

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<p>深層学習によって様々な分類問題が解決されているが，分類カテゴリ毎のデータ量が不均衡な問題を扱う場合，多くの課題がある．不均衡データへの対策として，少量カテゴリのデータ量を増加させ均衡化する手法がある．これをかさ増しと呼び画像処理分野ではノイズの付与や回転による方法が一般的である．最近ではGenerative Adversarial Network: GANによる画像生成手法を用いる場合がある．一方で，自然言語処理の分野では有効なかさ増し手法はいまだ確立されておらず，人手によるかさ増しが行われている．人手によるかさ増しではルールの設計など負担が大きく，機械的なかさ増し手法が必要となる．しかし，文章生成における機械的なかさ増しは画像生成に比べ不安定である．これは文章の特徴獲得の難しさが原因だと考えられる．そこで本論文ではグラフ情報に注目した機械学習による文章生成手法を提案する．CaboChaによって生成されたグラフ情報をGraph Convolutionにより畳み込み処理する．提案するGANにより生成されたかさ増し文章を3つの計算実験により評価し有効性を示した．</p>

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多様化する大学教育シリーズ(第1回)社会課題に取り組むワークショップとその効果 : 琉球大学・京都大学合同デザインスクールの経験

當間 愛晃, 山田 孝治, 遠藤 聡志, 十河 卓司, 石田 亨

電子情報通信学会誌 = The journal of the Institute of Electronics, Information and Communication Engineers ( 電子情報通信学会 )  102 ( 2 ) 172 - 178   2019.02 [ Peer Review Accepted ]

Type of publication: Research paper (scientific journal)

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本稿では，2013年から毎年実施している琉球大学・京都大学合同デザインスクールの経験を基に，社会課題に取り組むワークショップとその効果について述べる．取り組むテーマは毎年異なり，雇用問題や地方都市の活性化といった全国にもつながる本格的な問題を設定した．これまでの5年間で延べ158名の学生が参加し，沖縄・京都そして留学生といった異文化融合も含む横断討論を行い，互いの視野拡大・複合的な視点獲得を促進することで，多様なアイデアが生み出された．アンケートや追跡調査から，ワークショップ後の学びにも寄与する事例が現れ始めていることが分かった．

畳み込みニューラルネットワークを用いた表情表現の獲得と顔特徴量の分析

西銘 大喜, 遠藤 聡志, 當間 愛晃, 山田 孝治, 赤嶺 有平

人工知能学会論文誌 ( 社団法人 人工知能学会 )  32 ( 5 ) F - H34_1-8   2017

Type of publication: Research paper (scientific journal)

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<p>Facial expressions play an important role in communication as much as words. In facial expression recognition by human, it is difficult to uniquely judge, because facial expression has the sway of recognition by individual difference and subjective recognition. Therefore, it is difficult to evaluate the reliability of the result from recognition accuracy alone, and the analysis for explaining the result and feature learned by Convolutional Neural Networks (CNN) will be considered important. In this study, we carried out the facial expression recognition from facial expression images using CNN. In addition, we analysed CNN for understanding learned features and prediction results. Emotions we focused on are "happiness", "sadness", "surprise", "anger", "disgust", "fear" and "neutral". As a result, using 32286 facial expression images, have obtained an emotion recognition score of about 57%; for two emotions (Happiness, Surprise) the recognition score exceeded 70%, but Anger and Fear was less than 50%. In the analysis of CNN, we focused on the learning process, input and intermediate layer. Analysis of the learning progress confirmed that increased data can be recognised in the following order "happiness", "surprise", "neutral", "anger", "disgust", "sadness" and "fear". From the analysis result of the input and intermediate layer, we confirmed that the feature of the eyes and mouth strongly influence the facial expression recognition, and intermediate layer neurons had active patterns corresponding to facial expressions, and also these activate patterns do not respond to partial features of facial expressions. From these results, we concluded that CNN has learned the partial features of eyes and mouth from input, and recognise the facial expression using hidden layer units having the area corresponding to each facial expression.</p>

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Estimating Age on Twitter Using Self-Training Semi-Supervised SVM

Iju Tatsuyuki, Endo Satoshi, Yamada Koji, Toma Naruaki, Akamine Yuhei

人工生命とロボットに関する国際会議予稿集 ( 株式会社ALife Robotics )  21   228 - 231   2016.01

Type of publication: Research paper (scientific journal)

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The estimation methods for Twitter user's attributes typically require a vast amount of labeled data. Therefore, an efficient way is to tag the unlabeled data and add it to the set. We applied the self-training SVM as a semi-supervised method for age estimation and introduced Plat scaling as the unlabeled data selection criterion in the self-training process. We show how the performance of the self-training SVM varies when the amount of training data and the selection criterion values are changed.

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Feature Acquisition From Facial Expression Image Using Convolutional Neural Networks

Nishime Taiki, Endo Satoshi, Yamada Koji, Toma Naruaki, Akamine Yuhei

人工生命とロボットに関する国際会議予稿集 ( 株式会社ALife Robotics )  21   224 - 227   2016.01

Type of publication: Research paper (scientific journal)

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In this study, we carried out the facial expression recognition from facial expression dataset using Convolutional Neural Networks (CNN). In addition, we analyzed intermediate outputs of CNN. As a result, we have obtained a emotion recognition score of about 58%; two emotions (Happiness, Surprise) recognition score was about 70%. We also confirmed that specific unit of intermediate layer have learned the feature about Happiness. This paper details these experiments and investigations regarding the influence of CNN learning from facial expression.

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反応角度を自動調節可能なジョイスティック型コントローラの開発

比嘉 聖, 神里 志穂子, 山田 孝治, 眞喜志 隆, 佐竹 卓彦, 山田 親稔

電気学会論文誌. D,　産業応用部門誌 ( 一般社団法人 電気学会 )  136 ( 10 ) 703 - 710   2016

Type of publication: Research paper (scientific journal)

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<p>In nearby special support schools, the practice of driving a motorized wheelchair using a joystick has been conducted for physically disabled children. However, physically disabled children require support and adjustment of the equipment corresponding to their disabilities because it is difficult to operate a joystick in a specific direction owing to their disabilities. In this study, we develop a joystick-type controller that can be automatically adjusted to the reaction angle suitable for the actual conditions of physically disabled children. Moreover, we conduct a quantitative evaluation of upper limb motion when operating the joystick-type controller that we developed to examine the effectiveness of the proposed method. The evaluation results confirm an effective improvement in the operability when the acquired reaction angle is suitable for the actual conditions of the user by the proposed method.</p>

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A Study on Emotion Estimation of Narratives Using Cognitive Appraisals of the Reader

Naruaki Toma, Yuhei Akamine, Koji Yamada, Satoshi Endo

2016 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN, AND CYBERNETICS (SMC) ( IEEE )    572 - 576   2016 [ Peer Review Accepted ]

Type of publication: Research paper (scientific journal)

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Our emotion estimation refers to estimation of a reader's sentiments and feelings after they read a narrative (i.e., post-reading emotion types). The emotion types manifest in a reader's feelings combine to form diverse and various patterns. To elicit this phenomenon, we here attempt to estimate readers' emotional patterns based on their cognitive appraisals of the work. This paper describes our cognitive appraisal methodology, variation in readers' emotion types due to differences in their cognitive appraisals, and report and discuss the results of emotion estimation experiments in which a reader performs a cognitive appraisal of the text of a narrative.

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An Introduction of a Tag Ratio Model and the Classification Examination for Recommender Systems

Kazuki Yamauchia Naruaki Toma, Yuhei Akamine, Koji Yamada, Satoshi Endo

Procedia Computer Science ( ELSEVIER )  Vol.22   606 - 614   2013.10

Type of publication: Research paper (other science council materials etc.)

An Influence of Players Ballot-Weight Changing in Consultation Algorithm,

Keisuke Touma, Satoshi Endo, Naruaki Toma, Yuhei Akamine, Koji Yamada

Journal of Advanced Computational Intelligence and Intelligent Informatics ( FUJI TECHNOLOGY PRESS )  Vol.17 ( No.5 ) 707 - 714   2013.09 [ Peer Review Accepted ]

Type of publication: Research paper (other science council materials etc.)

Effect of Potential Model on Monte-Carlo Go: Pruning the igo Game Tree Using Potential and Potential Gradient

Makoto Oshima, Koji Yamada, Satoshi Endo

Advances in Intelligent Systems and Computing 194: Intelligent Autonomous Systems 12 ( Springer )  194 ( 2 ) 767 - 774   2013.01 [ Peer Review Accepted ]

Type of publication: Research paper (other science council materials etc.)

Effect of Potential Model Pruning on Different-Sized Boards in Monte-Carlo GO

Makoto Oshima, Koji Yamada, Satoshi Endo

IJCSNS International Journal of Computer Science and Network Security ( IJCSNS )  Vol.12 ( No.11 )   2012.11 [ Peer Review Accepted ]

Type of publication: Research paper (other science council materials etc.)

A potential model pruning in Monte-Carlo go

Makoto Oshima, Koji Yamada, Satoshi Endo

Proceedings of the 17th International Symposium on Artificial Life and Robotics (AROB 17th 2012) ( IEEE )    722 - 725   2012.01 [ Peer Review Accepted ]

Type of publication: Research paper (other science council materials etc.)

Basic Research on Speed-Up of Reinforcement Learning Using Parallel Processing for Combination Value Function

Tsuguhisa Touma，Yuuki Nakama，Koji Yamada，Satoshi Endo

Procedia Compluter Science ( ELSEVIER )  Vol.6   183 - 188   2011.10 [ Peer Review Accepted ]

Type of publication: Research paper (other science council materials etc.)

Probability of Potential Model Pruning in Monte-Carlo Go

Makoto Oshima, Koji Yamada, Satoshi Endo

Procedia Compluter Science ( ELSEVIER )  Vol.6   237 - 242   2011.10 [ Peer Review Accepted ]

Type of publication: Research paper (other science council materials etc.)

Competitive Coevolutionary Algorithm with Potential Model for the Tsumego Game

Makoto Oshima, Koji Yamada, Satoshi Endo

Joint 5th International Conference on Soft Computing and Intelligent Systems and 11th International Symposium on Advanced Intelligent Systems (SCIS ( その他の出版社 )    2010.12 [ Peer Review Accepted ]

Type of publication: Research paper (other science council materials etc.)

Competitive Coevolutionary Algorithm with Electric Charge Model for the Tsume-go Game

Makoto Oshima, Koji Yamada, Satoshi Endo

Intelligent Engineering Systems Through Artificial Neural Networks, Volume 20,(editor C.H.Dagli et al) ( ASME PRESS )  Vol.20   179 - 186   2010.11 [ Peer Review Accepted ]

Type of publication: Research paper (other science council materials etc.)