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All Technical Committee Conferences (Searched in: All Years)
| Committee | Date Time | Place | Paper Title / Authors | Abstract | Paper # | |
| ICSS, IPSJ-SPT | 2024-03-22 11:20 |
Okinawa | OIST (Primary: On-site, Secondary: Online) |
Evaluation of Feature Inference Risk from Explainable AI metrics LIME and Shapley Values Ryotaro Toma, Hiroaki Kikuchi (Meiji Univ.)  ICSS2023-88 |
Explainability has gained attention to ensure fairness and transparency in machine learning models, providing users with... [more] | ICSS2023-88 pp.137-144 |
| SIS | 2024-03-14 14:30 |
Kanagawa | Kanagawa Institute of Technology (Primary: On-site, Secondary: Online) |
Explainability for Graph-based Fake News Detection using Topic and Propagation-aware Visualization Kayato Soga, Soh Yoshida, Mitsuji Muneyasu (Kansai Univ.) SIS2023-49 |
Based on the observation that the structure of information propagation networks differs from that of real news, methods ... [more] | SIS2023-49 pp.21-26 |
| PRMU, MVE, VRSJ-SIG-MR, IPSJ-CVIM | 2024-01-26 15:46 |
Kanagawa | Keio Univ. (Hiyoshi Campus) | PRMU2023-48 |
In the realm of autonomous driving, end-to-end models (E2EDMs) have gained prominence due to their high predictive accur... [more] | PRMU2023-48 pp.46-49 |
| SIP, IT, RCS | 2024-01-19 14:30 |
Miyagi | (Primary: On-site, Secondary: Online) |
Infant Detection in Passenger Vehicles Using Millimeter Wave FMCW-MIMO Radar and CFAR Algorithm Kotone Sato, Steven Wandale, Koichi Ichige (Yokohama National Univ.), Kazuya Kimura, Ryo Sugiura (Murata Manufacturing) IT2023-71 SIP2023-104 RCS2023-246 |
This paper implements several proposed features using the CFAR algorithm, then constructs a concise decision tree model ... [more] | IT2023-71 SIP2023-104 RCS2023-246 pp.223-228 |
| MI | 2023-05-18 15:30 |
Aichi | Nagoya Congress Center | Grad-CAM approach for Multiclass Magnetic Resonance Imaging Tumor detection and Classification Tahir Hussain, Shouno Hayaru (UEC) MI2023-4 |
The growth of abnormal cells in the human brain causes brain tumors (BT). Early diagnosis becomes essential for timely t... [more] | MI2023-4 pp.10-13 |
| IBISML | 2022-01-18 11:15 |
Online | Online | [Invited Talk]
TBA Jun Sakuma (Tsukuba Univ./RIKEN) |
Explainability is one of the key elements required in medical image diagnosis using deep image recognition models. In th... [more] | |
| ET | 2021-12-11 13:00 |
Online | Online | Development of trait-based neural automated essay scoring incorporating multidimensional item response theory Takumi Shibata, Masaki Uto (UEC) ET2021-33 |
In recent years, deep neural network (DNN)-based automated essay scoring (AES) models that can simultaneously predict th... [more] | ET2021-33 pp.23-28 |
| SWIM | 2021-11-27 14:10 |
Online | Online | Studies of maximum electricity forecasting model including electricity market price
-- Time series analysis with extra regressors added -- Hiroyuki Ogura (Nihon Univ.), Shunsuke Managi (Kyushu Univ.) SWIM2021-27 |
As one of the solutions to the difficult problem of achieving both stable electricity supply and decarbonization, improv... [more] | SWIM2021-27 pp.7-14 |
| MVE, IMQ, IE, CQ (Joint) [detail] |
2021-03-03 14:40 |
Online | Online | Semantic and Quantitative Explanation for Networks using Feature Interaction Bohui Xia, Xueting Wang, Toshihiko Yamasaki (The Univ. of Tokyo) IMQ2020-35 IE2020-75 MVE2020-67 |
Deep learning-based methods have shown remarkable performances in many tasks. However, it is hard for us to interpret th... [more] | IMQ2020-35 IE2020-75 MVE2020-67 pp.127-132 |
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