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All Technical Committee Conferences (Searched in: All Years)
| Committee | Date Time | Place | Paper Title / Authors | Abstract | Paper # | |
| KBSE | 2024-01-24 09:10 |
Kagoshima | (Primary: On-site, Secondary: Online) |
Datetime Feature Recommendation System by Using Data Column Names Satoshi Masuda, Tomohiro Takeda (TCU)  KBSE2023-58 |
Analysis to gain new knowledge from huge amounts of data is called data science, and its widespread use is now socially ... [more] | KBSE2023-58 pp.43-48 |
| ET | 2023-11-11 14:50 |
Kagawa | Kagawa University Saiwai-cho (Main) Campus / Online (Primary: On-site, Secondary: Online) |
Uncertainty Estimation in Neural Automatic Scoring Applying Multitask Learning of Regression and Classification Yuto Takahashi, Masaki Uto (UEC) ET2023-31 |
In writing tests, grading by humans can be expensive and is not always sufficiently accurate. To resolve this problem, a... [more] | ET2023-31 pp.40-46 |
| SP, IPSJ-MUS, IPSJ-SLP [detail] | 2022-06-17 15:00 |
Online | Online | Representation and analytical normalization for vocal-tract-length transformation by group theory Atsushi Miyashita, Tomoki Toda (Nagoya Univ) SP2022-11 |
In automatic speech recognition, a recognition result should be invariant with respect to acoustic changes caused by dif... [more] | SP2022-11 pp.41-46 |
| SeMI, IPSJ-DPS, IPSJ-MBL, IPSJ-ITS | 2022-05-26 09:45 |
Okinawa | (Primary: On-site, Secondary: Online) |
Evaluation of Handwritten Numerical Character Recognition by Concatenated LSTM with Multiple Subjects Noriaki Kaneko, Masakatsu Ogawa (Sophia Univ.) SeMI2022-1 |
With the increasing infection of the new coronavirus (COVID-19), demand for contactless technology is rapidly increasing... [more] | SeMI2022-1 pp.1-4 |
| NLC | 2022-03-07 15:50 |
Online | Online | Simile identification based on machine learning using pseudo data acquisition Jintaro Jimi, Kazutaka Shimada (Kyutech) NLC2021-36 |
Simile is a kind of figurative language. It expresses the target of the figurative language by using comparators such a... [more] |
NLC2021-36 pp.48-53 |
| MI | 2022-01-26 11:05 |
Online | Online | Study on automatic generation of COVID-19 related radiology reports from chest CT images Shinji Okazaki, Yuichiro Hayashi, Masahiro Oda (Nagoya Univ.), Masahiro Hashimoto, Masahiro Jinzaki (Keio Univ.), Toshiaki Akashi, Shigeki Aoki (Juntendo Univ.), Kensaku Mori (Nagoya Univ./NII) MI2021-57 |
In this paper, we describe a study on automatic generation of COVID-19 related radiology reports from chest CT images. T... [more] | MI2021-57 pp.49-54 |
| RCS, SIP, IT | 2022-01-20 14:05 |
Online | Online | Automatic Modulation Classification Based on SNR estimation using Multi-Task Learning Wataru Machida, Yosuke Sugiura, Nozomiko Yasui, Tetsuya Shimamura (Saitama Univ.) IT2021-56 SIP2021-64 RCS2021-224 |
Automatic modulation classification is a technology that identifies the modulation type used in received signals and pla... [more] | IT2021-56 SIP2021-64 RCS2021-224 pp.155-160 |
| ICM | 2021-03-19 09:50 |
Online | Online | Evaluation of automatic generation method of network failure point estimation rule Fumika Asai, Norio Yamamoto, Shunsuke Kanai, Haruhisa Nozue, Kenichi Tayama (NTT) ICM2020-67 |
It is important to identify the suspected failure point quickly in order to realize the early restoration in the failure... [more] | ICM2020-67 pp.42-47 |
| PRMU, IPSJ-CVIM | 2021-03-05 10:00 |
Online | Online | Automatic music transcription system based on convolutional neural network for electric guitar considering sounds of same pitch and different strings Toshiaki Matsui, Tetsuya Matsumoto, Hiroaki Kudo (Nagoya Univ), Yoshinori Takeuchi (Daido Univ) PRMU2020-86 |
In this research, we propose a system that outputs tablature notation of an electric guitar performance from acoustic si... [more] | PRMU2020-86 pp.97-102 |
| SP, EA, SIP | 2020-03-02 15:45 |
Okinawa | Okinawa Industry Support Center (Cancelled but technical report was issued) |
Performance evaluation of distilling knowledge using encoder-decoder for CTC-based automatic speech recognition systems Takafumi Moriya, Hiroshi Sato, Tomohiro Tanaka, Takanori Ashihara, Ryo Masumura, Yusuke Shinohara (NTT) EA2019-131 SIP2019-133 SP2019-80 |
We present a novel training approach for connectionist temporal classification (CTC) -based automatic speech recognition... [more] | EA2019-131 SIP2019-133 SP2019-80 pp.175-180 |
| NLC, IPSJ-DC | 2019-09-27 10:35 |
Tokyo | Future Corporation | Automatic Detection of Unfair Sentences in Terms of Service Keiko Aoyama, Yasuhiro Ogawa, Takahiro Komamizu, Katsuhiko Toyama (Nagoya Univ.) NLC2019-8 |
Many users skip the terms of service (ToS) since they have many sentences and take time to read. However, they may inclu... [more] | NLC2019-8 pp.1-6 |
| NLC, IPSJ-ICS | 2019-06-21 15:40 |
Hiroshima | Hiroshima University of Economics (Tatemachi Campus) | Semi-Automatic Labeling for Emotion Classification with Deep Learning Kyosuke Masuda, Hiromitsu Nishizaki (Univ. of Yamanashi) NLC2019-5 |
We previously considered that the emotional classification method based on deep learning for tweets on social networking... [more] | NLC2019-5 pp.29-33 |
| KBSE | 2019-01-26 17:05 |
Tokyo | NII | Automatic book classification using neural networks Haruki Sugiyama, Yoshinori Tanabe (Tsurumi Univ.) KBSE2018-53 |
There are many studies applying machine learning to classify books by the Nippon Decimal Classification (NDC), a system ... [more] | KBSE2018-53 pp.61-66 |
| SANE | 2018-10-12 13:30 |
Tokyo | The University of Electro-Communications | Automatic Target Recognition based on Generative Adversarial Networks for Synthetic Aperture Radar Images Yang-Lang Chang, Bo-Yao Chen, Chih-Yuan Chu, Sina Hadipour (NTUT), Hirokazu Kobayashi (OIT) SANE2018-51 |
Synthetic Aperture Radar (SAR) is an all day and all weather condition imaging technique which is widely used in nationa... [more] | SANE2018-51 pp.41-44 |
| SANE | 2018-05-14 11:50 |
Tokyo | Kikai-Shinko-Kaikan Bldg. | SAVERS: SAR ATR with Verification Support Based on Convolutional Neural Network Hidetoshi Furukawa SANE2018-5 |
We propose a new convolutional neural network (CNN) which performs coarse and fine segmentation for end-to-end synthetic... [more] | SANE2018-5 pp.23-28 |
| SANE | 2018-01-25 14:50 |
Nagasaki | Nagasaki Prefectural Art Museum | Deep Learning for End-to-End Automatic Target Recognition from Synthetic Aperture Radar Imagery Hidetoshi Furukawa (Toshiba Infrastructure Systems & Solutions) SANE2017-92 |
The standard architecture of synthetic aperture radar (SAR) automatic target recognition (ATR) consists of three stages:... [more] | SANE2017-92 pp.35-40 |
| SANE | 2017-08-24 13:50 |
Osaka | OIT UMEDA Campus | Deep Learning for Target Classification from SAR Imagery
-- Data Augmentation and Translation Invariance -- Hidetoshi Furukawa (Toshiba Infrastructure Systems & Solutions) SANE2017-30 |
This report deals with translation invariance of convolutional neural networks (CNNs) for automatic target recognition (... [more] | SANE2017-30 pp.13-17 |
| LOIS | 2017-03-03 16:40 |
Okinawa | N.Ohama Memorial Hall | Availability of Classifier of Information for "Palatability" in Microblogs Maki Morita (Wakayama Univ.), Eiji Aramaki (NAIST), Akiyo Nadamoto (Konan Univ.), Mai Miyabe (Wakayama Univ.) LOIS2016-103 |
The restaurant information searches on Internet are widely available now, but such searches have problems of providing u... [more] | LOIS2016-103 pp.229-234 |
| IN | 2017-01-20 10:20 |
Aichi | Spatio-Temporal Emotion Estimation for Automatic Map Generation of Emotion Distributions Satoru Watanabe, Komei Arasawa, Motoki Eida, Syun Hattori (Muroran Inst. of Tech.) IN2016-94 |
A certain place gives an effect on its visitor's emotion. For instance, a person who is tired of work climbs Mt. Fuji an... [more] | IN2016-94 pp.55-60 |
|
| NLC, TL | 2016-06-05 10:20 |
Hokkaido | Otaru University of Commerce | A Comparative Analysis of Sizzle words for Automatic Extraction of "Palatability" Maki Morita (Wakayama Univ.), Eiji Aramaki (NAIST), Akiyo Nadamoto (Konan Univ.), Mai Miyabe (Wakayama Univ.) TL2016-11 NLC2016-11 |
Nowadays, the restaurant search services on the Internet become popular, people use them when they search the new restau... [more] | TL2016-11 NLC2016-11 pp.53-58 |
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