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All Technical Committee Conferences (Searched in: Recent 10 Years)
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Search Results: Conference Papers |
Conference Papers (Available on Advance Programs) (Sort by: Date Descending) |
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Committee |
Date Time |
Place |
Paper Title / Authors |
Abstract |
Paper # |
DE, IPSJ-DBS, IPSJ-IFAT |
2024-12-26 13:30 |
Online |
Online (Online) |
DE2024-14 |
There are soft clustering methods such as Fuzzy C-means that take into account the possibility of multiple labels belong... [more] |
DE2024-14 pp.13-18 |
PRMU, IPSJ-CVIM, IPSJ-DCC, IPSJ-CGVI |
2023-11-16 16:50 |
Tottori |
(Tottori, Online) (Primary: On-site, Secondary: Online) |
On Food Plant Classification from Luehdorfia Japonica Images using Multi-label Classification ABN Tsubasa Hirakawa, Takaaki Arai, Takayoshi Yamashita, Hironobu Fujiyoshi, Yuichi Oba, Hiromichi Fukui (Chubu Univ.), Masaya Yago (Tokyo Univ.) PRMU2023-27 |
Butterfly is a familiar taxon. Because of the abundance of specimens and the ease of comparison between specimens, regio... [more] |
PRMU2023-27 pp.62-67 |
NLC, IPSJ-ICS |
2022-07-08 15:55 |
Online |
Online (Online) |
Topic Classification of Kyutech Corpus by Machine Learning Shinnosuke Kawasaki, Kazutaka Shimada (Kyutech) NLC2022-3 |
Discussion summarization is one of the most important tasks for discussion analysis.
Utterances in a discussion contain... [more] |
NLC2022-3 pp.13-18 |
NLC, IPSJ-NL, SP, IPSJ-SLP [detail] |
2021-12-03 16:10 |
Online |
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 |
MI |
2021-03-16 09:15 |
Online |
Online (Online) |
Tuberculosis in Chest CT Image Analysis based on multi-axis projections using Deep learning Tetsuya Asakawa, Masaki Aono (Toyohashi Univ) MI2020-64 |
The purpose of this research is to make accurate estimates for the six labels (Left affected, Right affected, Light ple... [more] |
MI2020-64 pp.74-79 |
SP |
2019-08-28 17:00 |
Kyoto |
Kyoto Univ. (Kyoto) |
Speech Emotion Classification based on Multi-Label Emotion Existence Estimation Atsushi Ando, Ryo Masumura, Hosana Kamiyama, Satoshi Kobashikawa, Yushi Aono (NTT) SP2019-16 |
This paper presents a novel speech emotion classification that addresses the ambiguous nature of emotions in speech. Mos... [more] |
SP2019-16 pp.39-44 |
PRMU |
2017-10-12 14:30 |
Kumamoto |
(Kumamoto) |
Generalized Subclass Method for Multi-label Classification Batzaya Norov-Erdene, Mineichi Kudo (Hokkaido Univ.) PRMU2017-74 |
Multi-label classification (MLC) problems are emerging in medical diagnosis, web page annotation, image annotation, etc.... [more] |
PRMU2017-74 pp.67-72 |
ITS, IE, ITE-AIT, ITE-HI, ITE-ME, ITE-MMS, ITE-CE [detail] |
2016-02-23 10:15 |
Hokkaido |
Hokkaido Univ. (Hokkaido) |
Refinement of Multi-Label Classification Results using Class Relations Based on Higher-Order MRF Ryosuke Furuta, Yusuke Fukushima, Toshihiko Yamasaki, Kiyoharu Aizawa (UT) ITS2015-76 IE2015-118 |
In multi-label classication problems, in which multiple labels are estimated for an input data, the simplest way is to ... [more] |
ITS2015-76 IE2015-118 pp.241-246 |
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