Papers - Okada Yoshifumi

1. Cake Moisture Estimation Based on Image Analysis and Regression Model for Controlling the Compression Time of Filter Press in Sludge Dewatering

   Poltak Sandro Rumahorbo, Nobuhiro Yazawa, Hiroki Ito, Jun Sugimoto, Satoshi Kondo, Yoshifumi Okada, Kazuhiko Sato, Warut Timprae, Shinya Watanabe，Processes，vol.13，(6)，Article Number:1919，2025.06

   

2. CNDD-Net: A Lightweight Attention-Based Convolutional Neural Network for Classifying Corn Nutritional Deficiencies and Leaf Diseases

   Suresh Timilsina, Sandhya Sharma, Samir Gnawali, Kazuhiko Sato, Yoshifumi Okada, Shinya Watanabe, Satoshi Kondo，electronics，vol.14，(7)，2025.04

   

3. Preprocessing-Free Convolutional Neural Network Model for Arrhythmia Classification Using ECG Images

   Chotirose Prathom, Ryuhi Fukuda, Yuto Yokoyanagi, and Yoshifumi Okada，Technologies，vol.13，(4)，2025.03

   

4. Toward Personal Identification Using Multi-Angle-Captured Ear Images: A Feasibility Study

   Ryuhi Fukuda, Yuto Yokoyanagi, Chotirose Prathom, and Yoshifumi Okada，Applied Sciences，vol.15，(6)，2025.03

   

5. Development of Efficient and Robust Linkage Pattern Mining for Multiple Sequential Data

   Kyosuke Maeda, Issei Yokota, Yoshifumi Okada, and Saerom Lee，IAENG International Journal of Computer Science，vol.52，(1)，(p.223 ～ 232)，2025.01

   

6. Developing an Alert System for Agricultural Protection: Sika Deer Detection Using Raspberry Pi

   Sandhya Sharma, Buchaputara Pansri, Suresh Timilsina, Bishnu Prasad Gautam, Yoshifumi Okada, Shinya Watanabe,Satoshi Kondo, Kazuhiko Sato，electronics，vol.13，(23)，2024.12

   

7. Multi-Input Speech Emotion Recognition Model Using Mel Spectrogram and GeMAPS

   Itsuki Toyoshima, Yoshifumi Okada, Momoko Ishimaru, Ryunosuke Uchiyama, and Mayu Tada，Sensors，vol.23，(3)，2023.02

   

8. A New Regression Model for Depression Severity Prediction Based on Correlation among Audio Features Using a Graph Convolutional Neural Network

   1) Momoko Ishimaru, Yoshifumi Okada, Ryunosuke Uchiyama, Ryo Horiguchi, and Itsuki Toyoshima，Diagnostics，vol.13，(4)，2023.02

   

9. Classification of Depression and Its Severity Based on Multiple Audio Features Using a Graphical Convolutional Neural Network

   Momoko Ishimaru, Yoshifumi Okada, Ryunosuke Uchiyama, Ryo Horiguchi, Itsuki Toyoshima，International Journal of Environmental Research and Public Health，vol.20，(2)，2023.01

   

10. Educational Recommendation System Utilizing Learning Styles: A Systematic Literature Review

    Vivat Thongchotchat, Yasuo Kudo, Yoshifumi Okada, and Kazuhiko Sato，IEEE Access，vol.11，(p.8988 ～ 8999)，2023.01

    

11. End-to-End Convolutional Neural Network Model to Detect and Localize Myocardial Infarction Using 12-Lead ECG Images without Preprocessing

    Ryunosuke Uchiyama, Yoshifumi Okada, Ryuya Kakizaki and Sekito Tomioka，Bioengineering-Basel，vol.9，(9)，2022.09

    

12. Identifying Voice Individuality Unaffected by Age-Related Voice Changes during Adolescence

    Natsumi Suzuki, Momoko Ishimaru, Itsuki Toyoshima, and Yoshifumi Okada. ，Sensors，vol.22，(4)，2022.02

    

13. Missing Value Imputation Method for Multiclass Matrix Data Based on Closed Itemset

    Mayu Tada, Natsumi Suzuki, and Yoshifumi Okada，Entropy，vol.24，(2)，2022.02

    

14. An Association Analysis of Shop Owners' Mental Factors for Introducing Mobile Payment Systems

    Zijie Zhang, Tanapun Srichanthamit, Ponnapa Musikapun, Yoshifumi Okada, Hidetsugu Suto，The Transactions of Human Interface Society，vol.23，(4)，(p.481 ～ 488)，2021.11

    

15. Linkage Pattern Mining using Interval and Order of Pattern Appearance

    Saerom Lee, Kaiji Sugimoto, and Yoshifumi Okada，IAENG International Journal of Computer Science，vol.46，(4)，(p.691 ～ 698)，2019.11

    

16. Detection and localization of myocardial infarction based on a convolutional autoencoder

    Kaiji Sugimoto, Yudai Kon, Saerom Lee, and Yoshifumi Okada，Knowledge-based systems，vol.178，(p.123 ～ 131)，2019.08

    

17. A Recommender System based on an Improved Simultaneous Selection Method of Query Items and Neighbors

    Koki Miura, Mitsuru Takeuchi, and Yoshifumi Okada， IAENG International Journal of Computer Science，vol.43，(4)，(p.406 ～ 410)，2016.11

    

18. Linkage Pattern Mining Method for Multiple Sequential Data with Noise

    Saerom Lee, Takahiro Miura, Yusuke Okubo, and Yoshifumi Okada，IAENG International journal of computer science，vol.42，(4)，(p.361 ～ 367)，2015.11

    

19. 主体的学習を促す「与えない」演習の実践

    佐藤和彦，倉重健太郎，寺本渉，岡田吉史，工藤康生，佐賀聡人，工学教育，vol.61，(3)，(p.56 ～ 61)，2013.05

    

20. Detection of Linkage Patterns Repeating across Multiple Sequential Data

    Takahiro Miura and Yoshifumi Okada，International journal of computer applications，vol.63，(3)，(p.14 ～ 17)，2013.02