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All Technical Committee Conferences (Searched in: All Years)
| Committee | Date Time | Place | Paper Title / Authors | Abstract | Paper # | |
| SIP, IT, RCS | 2024-01-18 16:10 |
Miyagi | (Primary: On-site, Secondary: Online) |
A Study on Autoencoder for Iterative Signal Detection in MIMO Channels Yoshinori Ichihashi, Shinsuke Ibi (Doshisha Univ.), Takumi Takahashi (Osaka Univ.), Hisato Iwai (Doshisha Univ.)  IT2023-52 SIP2023-85 RCS2023-227 |
In this paper, we apply deep unfolding to uplink signal detection via probabilistic data association (PDA) and configure... [more] | IT2023-52 SIP2023-85 RCS2023-227 pp.115-120 |
| IBISML | 2023-12-20 16:25 |
Tokyo | National Institute of Informatics (Primary: On-site, Secondary: Online) |
Anomaly detection by deep support data descriptions with pseudo-anomaly data Shuta Tsuchio, Takuya Kitamura (NIT, Toyama college) IBISML2023-34 |
This paper presents deep support vector data description (DSVDD) with pseudo-anomaly data that generated by generative m... [more] | IBISML2023-34 pp.25-30 |
| IBISML | 2023-12-21 10:30 |
Tokyo | National Institute of Informatics (Primary: On-site, Secondary: Online) |
Badminton Rally Analysis Using LSTM Atsushi Yoshinaga, Masato Kiyama, Motoki Amagasaki (Kumamoto Univ.) IBISML2023-35 |
In this study, we analyze badminton rallies as a tactical support technology for sports using AI. In badminton, it is re... [more] | IBISML2023-35 pp.31-36 |
| CS | 2023-11-09 10:55 |
Shizuoka | Plaza Verde | Deep Joint Source-Channel Coding using Overlap Image Division for Block Noise Reduction Ryunosuke Yamamoto, Yoshiaki Inoue, Daisuke Hisano (Osaka Univ.) CS2023-65 |
Deep Joint Source-Channel Coding (Deep JSCC), which uses deep learning to perform source and channel coding simultaneous... [more] | CS2023-65 pp.16-18 |
| RCS, SAT (Joint) |
2023-08-31 10:55 |
Nagano | Naganoken Nokyo Building, and online (Primary: On-site, Secondary: Online) |
A study on source data and decoder of multitask CSI feedback method in FDD Massive MIMO Mayuko Inoue, Tomoaki Ohtsuki (Keio Univ.) RCS2023-102 |
In frequency-division duplex (FDD) massive multiple-input multiple-output (MIMO) systems, it is necessary to obtain down... [more] | RCS2023-102 pp.5-8 |
| CQ, MIKA (Joint) |
2023-08-31 15:55 |
Fukushima | Tenjin-Misaki Sports Park | Semantic Communication with Masked Autoencoders: Enhancing Efficiency in Image Transmission Jiale Wu, Zhaoyang Du, Celimuge Wu, Tsutomu Yoshinaga (UEC) CQ2023-29 |
Semantic communication, a promising candidate for 6G technology, has become a research hot spot. However, existing studi... [more] | CQ2023-29 pp.20-25 |
| EMM, BioX, ISEC, SITE, ICSS, HWS, IPSJ-CSEC, IPSJ-SPT [detail] | 2023-07-24 14:00 |
Hokkaido | Hokkaido Jichiro Kaikan | Non-profiled Side-channel Attacks by using Clustering Scores in Deep Learning model (1)
-- Attacks by using Auto Encoder against hardware-implemented AES -- Mizuki Nagahisa, Fukuda Yuta, Yoshida Kota, Fujino Takeshi (Ristumei Univ) ISEC2023-14 SITE2023-8 BioX2023-17 HWS2023-14 ICSS2023-11 EMM2023-14 |
In 2019, Differential Deep Learning Analysis (DDLA) was proposed as a deep-learning based side-channel attack in non-pro... [more] | ISEC2023-14 SITE2023-8 BioX2023-17 HWS2023-14 ICSS2023-11 EMM2023-14 pp.1-6 |
| SIS, IPSJ-AVM [detail] | 2023-06-15 11:35 |
Shimane | NIT, Matsue College (Primary: On-site, Secondary: Online) |
Detection of Calcification Regions from Dental Panoramic Radiograph Based on Semantic Segmentation Using Transformers Taito Murano, Mitsuji Muneyasu, Soh Yoshida, Akira Asano (Kansai Univ.), Keiichi Uchida (Matsumoto Dental Univ. Hospital,) SIS2023-3 |
Calcification regions, considered a sign of atherosclerosis, are sometimes observed in the carotid arteries in dental pa... [more] | SIS2023-3 pp.13-18 |
| SeMI, IPSJ-ITS, IPSJ-MBL, IPSJ-DPS | 2023-05-19 10:20 |
Okinawa | Okinawa Institute of Science and Technology (OIST) (Primary: On-site, Secondary: Online) |
Evaluation of Multi-edge Object Detection System using Deep Feature Compression Transmission Kohji Yamada, Yuichiro Kora, Meguru Yamazaki, Xuying Lei (Fujitsu) SeMI2023-13 |
Collaborative Intelligence has been proposed to divide DNN model and perform inferences collaborating on edge and cloud.... [more] | SeMI2023-13 pp.53-57 |
| MI | 2023-03-06 13:41 |
Okinawa | OKINAWA SEINENKAIKAN (Primary: On-site, Secondary: Online) |
Comparative study of the Small Intestine segmentation based on 2D and 3D U-Nets Qin An (Nagoya Univ.), Hirohisa Oda (UoS), SiRui Chen, Yuichiro Hayashi (Nagoya Univ.), Takayuki Kitasaka (Aichi Institute Univ), Aitaro Takimoto, Akinari Hinoki, Hiroo Uchida (Nagoya Univ.), Kojiro Suzuki (Aichi Medical Univ.), Masahiro Oda, Kensaku Mori (Nagoya Univ.) MI2022-82 |
In this paper, we aim to compare and analyze the small intestine segmentation methods based on U-Net and 3D U-Net. Segme... [more] | MI2022-82 pp.46-51 |
| MW | 2023-03-02 10:40 |
Tottori | Tottori Univ. (Primary: On-site, Secondary: Online) |
Memory-Driven MLP-Mixer Deep Learning Model for Intelligent Reflecting Surface-Assisted mmWave Systems Beam Prediction Taisei Urakami, Haohui Jia, Na Chen, Minoru Okada (NAIST) MW2022-159 |
Although deep learning (DL) based beam prediction for intelligent reflecting surface (IRS)-assisted millimeter wave (mmW... [more] | MW2022-159 pp.13-18 |
| SIS | 2023-03-03 14:30 |
Chiba | Chiba Institute of Technology (Primary: On-site, Secondary: Online) |
[Tutorial Lecture]
On Semantic Image Processing with Autoencoder Hiroyuki Tsuji (KAIT) SIS2022-58 |
Variational Auto Encoder (VAE) has a conceptually well-structured latent space and can realize semantic image manipulati... [more] | SIS2022-58 pp.97-102 |
| SeMI, SeMI (Joint) |
2023-01-19 15:25 |
Tokushima | Naruto grand hotel (Primary: On-site, Secondary: Online) |
[Short Paper]
Multimodal Image Inpainting Using Camera Imagery and WiFi RSSI Cheng Chen, Takayuki Nishio (Tokyo Tech), Mehdi Bennis (Oulu Univ.), Jihong Park (Deakin Univ.) SeMI2022-83 |
This study demonstrates the feasibility of image inpainting using both visual information and radio frequency (RF) signa... [more] | SeMI2022-83 pp.51-53 |
| MBE, MICT, IEE-MBE [detail] | 2023-01-17 09:50 |
Saga | Oral Cytology Based on Representation Learning of Visually Salient Cells Kazuki Matsuo, Eiji Mitate, Tomoya Sakai (Nagasaki Univ.) MICT2022-44 MBE2022-44 |
We classify microscopically photographed cells for screening tests to find oral cancer in its early stages. Oral cancer ... [more] | MICT2022-44 MBE2022-44 pp.7-12 |
|
| MIKA (3rd) |
2022-10-13 11:10 |
Niigata | Niigata Citizens Plaza (Primary: On-site, Secondary: Online) |
[Poster Presentation]
Autoencoder-based Signal Quantizer for Fronthaul Capacity Reduction Shinnosuke Yagi, Daisuke Hisano (Osaka Univ.) |
A mobile base station (MBS) in Beyond 5G/6G era requires larger capacity, lower latency, and more expanding coverage tha... [more] | |
| SC | 2022-05-27 13:25 |
Online | Online | Improvement of Performance of Question and Answering System using Ontology Generation Ayato Kuwana, Incheon Paik (UoA) SC2022-7 |
Automating ontology generation from raw text corpus is required to meet the ontology demand. As an initial attempt of on... [more] | SC2022-7 pp.37-42 |
| SIP, BioX, IE, MI, ITE-IST, ITE-ME [detail] | 2022-05-20 16:20 |
Kumamoto | Kumamoto University Kurokami Campus (Primary: On-site, Secondary: Online) |
Visualization of Important Features for Classifier Decisions using Deep Image Synthesis Yushi Haku, Megumi Nakao, Tetsuya Matsuda (Kyoto Univ.) SIP2022-28 BioX2022-28 IE2022-28 MI2022-28 |
It is difficult to know the basis for the decisions of machine learning models, and it is necessary to provide a highly ... [more] | SIP2022-28 BioX2022-28 IE2022-28 MI2022-28 pp.144-149 |
| RCS, SR, SRW (Joint) |
2022-03-02 10:50 |
Online | Online | Pilot Pattern Design Method using Autoencoder for CDL Channels Yuta Yamada, Tomoaki Ohtsuki (Keio Univ.) RCS2021-253 |
In the pilot-based channel estimations, a large number of pilot signals enable an improvement in the channel estimation ... [more] | RCS2021-253 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 |
| EA, SIP, SP, IPSJ-SLP [detail] | 2022-03-02 11:35 |
Okinawa | (Primary: On-site, Secondary: Online) |
Study of Method for Improving Speech Intelligibility in Glossectomy Patients by Knowledge Distillation via Lip Features Kazushi Takashima, Masanobu Abe, Sunao Hara (Okayama Univ.) EA2021-81 SIP2021-108 SP2021-66 |
In this paper, we propose a voice conversion method for improving speech intelligibility uttered by glossectomy patients... [more] | EA2021-81 SIP2021-108 SP2021-66 pp.108-113 |
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