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All Technical Committee Conferences (Searched in: All Years)
| Committee | Date Time | Place | Paper Title / Authors | Abstract | Paper # | |
| PRMU, IBISML, IPSJ-CVIM [detail] | 2023-03-02 11:15 |
Hokkaido | Future University Hakodate (Primary: On-site, Secondary: Online) |
Dynamic Weight Scheduling for Long-tailed Visual Recognition Xinyuan Li (Ritsumeikan Univ.), Yu Wang (Hitotsubashi Univ.), Jien Kato (Ritsumeikan Univ.)  PRMU2022-78 IBISML2022-85 |
For long-tailed image recognition tasks, re-weighting is effective to alleviate data imbalance by assigning higher weigh... [more] | PRMU2022-78 IBISML2022-85 pp.107-110 |
| PRMU, IBISML, IPSJ-CVIM [detail] | 2023-03-02 16:40 |
Hokkaido | Future University Hakodate (Primary: On-site, Secondary: Online) |
Does the class imbalance in the pre-training always adversely affect transfer learning performance? Shojun Nakayama (Toshiba) PRMU2022-89 IBISML2022-96 |
In this work, we studied how class-imbalance in the pre-training affect to the accuracy of the transfer learning. We div... [more] | PRMU2022-89 IBISML2022-96 pp.151-156 |
| IE, ITS, ITE-MMS, ITE-ME, ITE-AIT [detail] | 2023-02-22 13:00 |
Hokkaido | Hokkaido Univ. | Assessment System of Remote Structured Interview using Bimodal Neural Network Shengzhou Yi (UTokyo), Toshiaki Yamasaki (Talent and Assessment), Toshihiko Yamasaki (UTokyo) ITS2022-67 IE2022-84 |
A structured interview is a data collection method that relies on asking questions in a set of order to eliminate subjec... [more] | ITS2022-67 IE2022-84 pp.141-146 |
| PRMU | 2022-09-14 11:00 |
Kanagawa | (Primary: On-site, Secondary: Online) |
Disease and severity classification of coffee leaf images by global low-level feature aggregation network Takuhiro Okada, Satoshi Iizuka, Kazuhiro Fukui (Univ. of Tsukuba) PRMU2022-14 |
Coffee leaf disease is one of the most important problems in coffee production. It is very important in the coffee produ... [more] | PRMU2022-14 pp.25-30 |
| MVE | 2022-09-09 10:00 |
Tokyo | (Primary: On-site, Secondary: Online) |
Presentation Slide Assessment System using Visual and Semantic Segmentation Features Shengzhou Yi (UTokyo), Junichiro Matsugami (Rubato), Toshihiko Yamasaki (UTokyo) MVE2022-13 |
In this paper, we present a new presentation slide assessment system that can consider structural features of the slides... [more] | MVE2022-13 pp.16-21 |
| NLC, IPSJ-NL, SP, IPSJ-SLP [detail] | 2021-12-03 16:10 |
Online | Online | Label smoothing with co-occurrences information for multi-label classification Yuki Yasuda, Taichi Ishiwatari, Taro Miyazaki, Jun Goto (NHK) NLC2021-27 SP2021-48 |
Imbalanced learning is one of the big issues in multi-label classification task. Training models using such imbalanced d... [more] | NLC2021-27 SP2021-48 pp.48-53 |
| MVE | 2021-09-17 13:00 |
Online | Online | Identifying Design Problems of Presentation Slides using a Bimodal Neural Network Shengzhou Yi (UTokyo), Junichiro Matsugami (Rubato), Toshihiko Yamasaki (UTokyo) MVE2021-12 |
Although millions of presentation slides are created every day in business and academia, there are only a limited number... [more] | MVE2021-12 pp.21-26 |
| SeMI, IPSJ-MBL, IPSJ-UBI [detail] | 2021-03-01 10:50 |
Online | Online | SeMI2020-60 |
When gas and liquid are flowing simultaneously inside a transport conduit, their spatial distribution is referred to as ... [more] | SeMI2020-60 pp.13-18 |
| IE, ITS, ITE-MMS, ITE-ME, ITE-AIT [detail] | 2021-02-19 14:05 |
Online | Online | [Special Talk]
A Note on Discrimination of Road Surface Conditions Based on Deep Learning Using Road Images Yuya Moroto, Keisuke Maeda, Takahiro Ogawa, Miki Haseyama (Hokkaido Univ.) |
In this paper, we study the discrimination of road surface conditions based on deep learning using images captured by fi... [more] | |
| AI | 2020-12-10 14:20 |
Shizuoka | Online and HAMAMATSU ACT CITY (Primary: On-site, Secondary: Online) |
Slide Design Assessment Featuring Visual and Structural Analysis Shengzhou Yi (UTokyo), Junichiro Matsugami (Rubato), Xueting Wang, Toshihiko Yamasaki (UTokyo) AI2020-3 |
Appealing design of presentation slides is a great way to make the presentation more attractive and easier to understand... [more] | AI2020-3 pp.13-18 |
| IBISML | 2020-03-11 10:45 |
Kyoto | Kyoto University (Cancelled but technical report was issued) |
Calibrated Surrogate Maximization of Linear-Fractional Utility in Binary Classification Han Bao (Univ. of Tokyo/RIKEN), Masashi Sugiyama (RIKEN/Univ. of Tokyo) IBISML2019-43 |
Complex classification performance metrics such as the F-measure and Jaccard index are often used to handle class imbala... [more] | IBISML2019-43 pp.71-78 |
| MI | 2020-01-29 13:20 |
Okinawa | OKINAWAKEN SEINENKAIKAN | Imbalanced Subarachnoid Hemorrhage data automatic detection by using SMOTE algorithm based on deep learning Zhongyang Lu, Masahiro Oda, Yuichiro Hayashi, Hayato Ito (Nagoya Univ), Takeyuki Watadani, Osamu Abe (Department of Radiology,The Univ of Tokyo Hospital), Masahiro Hashimoto, Masahiro Jinzaki (Department of Radiology,Keio Univ School of Medicine), Kensaku Mori (Nagoya Univ) MI2019-75 |
Based on deep learning techniques, the performance of image classification has made significant progress. Especially in ... [more] | MI2019-75 pp.47-52 |
| WIT, SP | 2019-10-26 17:00 |
Kagoshima | Daiichi Institute of Technology | Neural Whispered Speech Detection with Imbalanced Learning Takanori Ashihara, Yusuke Shinohara, Hiroshi Sato, Takafumi Moriya, Kiyoaki Matsui, Yoshikazu Yamaguchi (NTT) SP2019-26 WIT2019-25 |
In this paper, we present a neural whispered-speech detection technique that offers utterance-level classification of wh... [more] | SP2019-26 WIT2019-25 pp.51-56 |
| IBISML | 2017-11-09 13:00 |
Tokyo | Univ. of Tokyo | Semi-Supervised AUC Optimization based on Positive-Unlabeled Learning Tomoya Sakai, Gang Niu (UTokyo/RIKEN), Masashi Sugiyama (RIKEN/UTokyo) IBISML2017-40 |
Maximizing the area under the receiver operating characteristic curve (AUC) is a standard approach to imbalanced classif... [more] | IBISML2017-40 pp.39-46 |
| NC, IPSJ-BIO, IBISML, IPSJ-MPS [detail] | 2016-07-06 10:25 |
Okinawa | Okinawa Institute of Science and Technology | A Semi-supervised Learning Method for Imbalanced Binary Classification Akinori Fujino, Naonori Ueda (NTT) IBISML2016-3 |
This paper presents a semi-supervised learning method for imbalanced binary classification where the number of positive ... [more] | IBISML2016-3 pp.195-200 |
| DE, IPSJ-DBS, IPSJ-IFAT | 2015-08-05 13:00 |
Nara | Todaiji Culture Center | Empirical Study on Instance Selection from Healthcare Data Using Fuzzy Rough Sets Do Van Nguyen (KDDI R&D Labs), Keisuke Ogawa (KDDI), Kazunori Matsumoto, Masayuki Hashimoto (KDDI R&D Labs) DE2015-14 |
This research shows a study on issues that cause low performance in disease prediction such as overlap and imbalance and... [more] | DE2015-14 pp.19-24 |
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