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All Technical Committee Conferences (Searched in: All Years)
| Committee | Date Time | Place | Paper Title / Authors | Abstract | Paper # | |
| DE, IPSJ-DBS | 2023-12-26 14:00 |
Tokyo | Institute of Industrial Science, The University of Tokyo | Interpretation of unsupervised clustering based on XAI Yu Sasaki, Fumiaki Saitoh (CIT)  DE2023-28 |
Explainable Artificial Intelligence (XAI) aims to introduce transparency and interpretability into the decision-making o... [more] | DE2023-28 pp.1-6 |
| EMCJ | 2023-11-24 13:25 |
Tokyo | Kikai-Shinko-Kaikan (Primary: On-site, Secondary: Online) |
A Study on Explainability of Convolutional Neural Network Predicting Electric Characteristics of Automotive Wire Harness Based on Score Regression Activation Mapping (Score-RAM) Syumpei Ebina, Tadatoshi Sekine, Shin Usuki, Kenjiro T. Miura (Shizuoka Univ.) EMCJ2023-74 |
In this report, we propose score regression activation mapping (Score-RAM) based on explainable artificial intelligence.... [more] | EMCJ2023-74 pp.13-18 |
| KBSE, SC | 2023-11-18 10:20 |
Miyagi | Sento Kaikan | Towards Standardized Data Model for Service Recommendation Based on User Needs Takuya Nakata, Sinan Chen (Kobe Univ.), Sachio Saiki (Kochi Univ. of Tech.), Masahide Nakamura (Kobe Univ.) KBSE2023-44 SC2023-27 |
Due to the internet's proliferation, digital devices, and COVID-19's impact, online service use has soared, driving dema... [more] | KBSE2023-44 SC2023-27 pp.57-62 |
| MI | 2023-09-08 11:20 |
Osaka | (Primary: On-site, Secondary: Online) |
A Study on Identifying Gender Differences Using Deep Learning from Retinal Fundus Images Shota Tsutsui (Waseda Univ.), Ichiro Maruko, Moeko Kawai (TWMU), Yoichi Kato, Jun Ohya (Waseda Univ.) MI2023-17 |
Previous studies show that a properly designed and trained deep learning algorithm is capable to identify the gender of ... [more] | MI2023-17 pp.8-11 |
| DE | 2023-06-16 09:10 |
Tokyo | Musashino University (Primary: On-site, Secondary: Online) |
A POI recommendation method with explanatory nature for user's purpose based on online review information Hajjime Katayama, Taketoshi Ushiama (Kyushu Univ.) DE2023-2 |
In this study, we propose a method in which the purpose of searching for a POI is entered as a query, and a POI suitable... [more] | DE2023-2 pp.7-12 |
| PRMU, IBISML, IPSJ-CVIM [detail] | 2023-03-03 17:00 |
Hokkaido | Future University Hakodate (Primary: On-site, Secondary: Online) |
Explainable Deep Clustering for Wafer Defect Pattern Classification Yuki Okazaki, Hiroki Takahashi (The Univ. of Electro-Communications) PRMU2022-115 IBISML2022-122 |
Classification of specific defect patterns on semiconductor wafers is important in manufacturing processes. Recently, ma... [more] | PRMU2022-115 IBISML2022-122 pp.299-304 |
| PRMU | 2022-09-15 10:00 |
Kanagawa | (Primary: On-site, Secondary: Online) |
One-cut Network Pruning at Initialization with Explainable Image Concepts Yinan Yang (Rits Univ.), Ying Ji (Nagoya Univ.), Yu Wang (Hitotsubashi Univ.), Jien Kato (Rits Univ.) PRMU2022-18 |
Recent research investigates the feasibility of one-cut network pruning at initialization (OPAI). SNIP and GraSP are tw... [more] | PRMU2022-18 pp.49-54 |
| SIP | 2022-08-26 14:26 |
Okinawa | Nobumoto Ohama Memorial Hall (Ishigaki Island) (Primary: On-site, Secondary: Online) |
Generation method of Adversarial Examples using XAI Ryo Kumagai, Shu Takemoto, Yusuke Nozaki, Masaya Yoshikawa (Meijo Univ.) SIP2022-72 |
With the advancement of AI technology, AI can be applied to various fields. Therefore the accountability for the decisio... [more] | SIP2022-72 pp.115-120 |
| PRMU, IPSJ-CVIM | 2022-05-13 10:30 |
Aichi | Toyota Technological Institute | Visualization of Decision Rationale Using Social and Physical Attention Mechanisms in Human Trajectory Prediction Model Masahiro Kato, Norimichi Ukita (TTI) PRMU2022-3 |
There is a great deal of interest in explainable AI that clarifies the basis of decisions, such as why a model makes a p... [more] | PRMU2022-3 pp.12-17 |
| NS, IN (Joint) |
2022-03-10 11:00 |
Online | Online | Experimental Evaluation of Influence of Distributing Deep Learning-Based IDSs on Their Classification Accuracy and Explainability Ayaka Oki, Yukio Ogawa, Kaoru Ota, Mianxiong Dong (Muroran-IT) IN2021-33 |
Increased data traffic associated with the wide spread usage of IoT devices accentuates the risk of large-scale cyber at... [more] | IN2021-33 pp.13-18 |
| MBE, NC (Joint) |
2022-03-02 11:00 |
Online | Online | Learning of a stacked autoencoder with regularizers added to the cost function, evaluation of their effectiveness, and clarification of its information compression mechanism Masumi Ishikawa (Kyutech) NC2021-49 |
Deep learning has a serious drawback in that the resulting models tend to be a black box, hence hard to understand. A sp... [more] | NC2021-49 pp.17-22 |
| LOIS, ICM | 2022-01-27 15:25 |
Online | Online | [Invited Talk]
Cyber Security with Human-in-the-Loop Machine Learning Masato Uchida (Waseda Univ.) ICM2021-38 LOIS2021-36 |
There have been many studies on methods to detect various malicious activities in cyberspace using machine learning mode... [more] | ICM2021-38 LOIS2021-36 pp.31-33 |
| NLP, MICT, MBE, NC (Joint) [detail] |
2022-01-23 12:10 |
Online | Online | Deep learning of mixture of continuous and categorical data with regularizers added to the cost function and evaluation of the effectiveness of sparse modeling Masumi Ishikawa (Kyutech) NC2021-45 |
Deep learning has a serious drawback in that the resulting models tend to be a black box, hence hard to understand. A sp... [more] | NC2021-45 pp.65-70 |
| PRMU | 2021-12-16 16:45 |
Online | Online | Supervoxel-based Explanation for Action Recognition Ying Ji (Nagoya Univ.), Yu Wang (Ritsumeikan Univ.), Kensaku Mori (Nagoya Univ.), Jien Kato (Ritsumeikan Univ.) PRMU2021-42 |
Deep neural network has shown remarkable performance in various areas, including image classification, action recognitio... [more] | PRMU2021-42 pp.98-100 |
| SIS, ITE-BCT | 2021-10-08 10:00 |
Online | Online | [Tutorial Lecture]
The Past and The Future of Explainable AI Techniques Yoshitaka Kameya (Meijo Univ.) SIS2021-17 |
Machine learning models of high predictive performance, such as deep neural networks and ensemble models, now play a cen... [more] | SIS2021-17 pp.36-41 |
| TL | 2021-09-18 16:05 |
Online | Online | [Keynote Address]
Neural Network as an Explainable Human
-- A New Approach to Contrastive Studies -- Yugo Murawaki (Kyoto Univ.) TL2021-16 |
In this talk, I argue that techniques developed in the field of explainable AI (XAI) have potential applications in comp... [more] | TL2021-16 pp.23-27 |
| PRMU | 2020-12-18 17:00 |
Online | Online | An evaluation method of area detection AI based on contribution pattern variation with noise addition Yasuhide Mori, Naofumi Hama, Masashi Egi (Hitachi) PRMU2020-67 |
The processing of image recognition AI using machine learning is generally black-boxed, and grasping the operating chara... [more] | PRMU2020-67 pp.166-171 |
| NC, MBE (Joint) |
2020-03-06 14:55 |
Tokyo | University of Electro Communications (Cancelled but technical report was issued) |
Efficient cluster mapping for conditions of weather based on combination of self-organizing map and hierarchical clustering Kazuki Osawa, Keiji Kamei (NIT), Masumi Ishikawa (KIT) NC2019-113 |
Recently, applications of Deep Learning(AI) for solving social problems have been frequently proposed. However, there ar... [more] | NC2019-113 pp.213-218 |
| NC, MBE | 2019-12-06 16:30 |
Aichi | Toyohashi Tech | Explaining Neural Networks by using a multiple tree Shunya Sasaki, Masafumi Hagiwara (Keio Univ) MBE2019-58 NC2019-49 |
The existing Neural Networks (NNs) have a problem that it is difficult to explain the reasoning process and the grounds ... [more] | MBE2019-58 NC2019-49 pp.79-84 |
| PRMU, BioX | 2019-03-17 14:45 |
Tokyo | A Study of Business Interpretation Technique for AI Predictions Naoaki Yokoi, Masashi Egi (Hitachi, Ltd.) BioX2018-39 PRMU2018-143 |
(To be available after the conference date) [more] | BioX2018-39 PRMU2018-143 pp.61-66 |
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