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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 10:45 |
Hokkaido | Future University Hakodate (Primary: On-site, Secondary: Online) |
A Study on Trendy Style Learning and Recommendation in Digital Makeup System Yoshimi Sato, Nobutaka Kuroki, Masahiro numa (Kobe Univ.) |
(To be available after the conference date) [more] | |
| PRMU, IBISML, IPSJ-CVIM [detail] | 2023-03-02 17:00 |
Hokkaido | Future University Hakodate (Primary: On-site, Secondary: Online) |
Evaluation of Vision Transformer based Spatial Transformer Networks Yoshiharu Iwasaki (Ritsumeikan Univ.), Yu Wang (Hitotsubashi Univ.), Jien Kato (Ritsumeikan Univ.) |
(To be available after the conference date) [more] | |
| SP, IPSJ-SLP, EA, SIP [detail] | 2023-03-01 11:20 |
Okinawa | (Primary: On-site, Secondary: Online) |
A Study on Selective Fixed-Filter ANC Using 2D-CNN with Sliding DCT input Kenya Doi, Yoshinobu Kajikawa (KU) |
(To be available after the conference date) [more] | |
| IE, ITS, ITE-MMS, ITE-ME, ITE-AIT [detail] | 2023-02-22 10:45 |
Hokkaido | Hokkaido Univ. | A Study of Estimating 3D Skeleton of a Human Full-Body Using Images Acquired by Omnidirectional Cameras Attached to the Human Body and Deep Learning Yuta Arai, Jun Ohya (Waseda Univ.), Hiroyuki Ogata (Seikei Univ.), Seo Chanjin (Waseda Univ.) |
(To be available after the conference date) [more] | |
| IE, ITS, ITE-MMS, ITE-ME, ITE-AIT [detail] | 2023-02-22 11:00 |
Hokkaido | Hokkaido Univ. | Discussion and user study of displaying 360-degree video that follows RoI Yuuki Sawabe (UTokyo), Satoshi Ikehata (NII), Kiyoharu Aizawa (UTokyo) |
(To be available after the conference date) [more] | |
| SANE | 2022-12-16 10:45 |
Nagasaki | Nagasaki Public Hall (Primary: On-site, Secondary: Online) |
Machine learning for global detection of photovoltaic panel installation using Landsat-8 Imagery Ryo Ito, Ryu Sugimoto, Chiaki Tsutsumi, Ryosuke Nakamura (AIST)  SANE2022-77 |
Nowadays, free-and-open medium-resolution satellite imagery can be utilized for sustainable monitoring of global changes... [more] | SANE2022-77 pp.74-76 |
| CS, IE, IPSJ-AVM, ITE-BCT [detail] | 2022-11-24 15:20 |
Aichi | Nagoya Institute of Technology (Primary: On-site, Secondary: Online) |
Locating the Fruit to Be Harvested and Estimating their Cut Positions from RGBD Images Acquired by a Camera Moved along a Fixed Path Using a Mask-RCNN Based Method Wentao Zhao, Jun Ohya, Chanjin Seo, Takuya Otani, Taiga Tanaka, Koki Masaya, Atsuo Takanishi (Waseda Univ.), Shuntaro Aotake, Masatoshi Funabashi (SONY CSL) CS2022-55 IE2022-43 |
This paper proposes a Mask R-CNN[1] based method for locating fruits (tomatoes and yellow bell peppers, etc.) and estima... [more] | CS2022-55 IE2022-43 pp.39-44 |
| CCS | 2022-11-18 09:50 |
Mie | (Primary: On-site, Secondary: Online) |
Consideration of an indicator of the total channels suitable for CNN Chisato Takahashi, Kenya Jin'no (TCU) CCS2022-54 |
Neural Architecture Search (NAS), which aims to automatically optimize the structure in order to search for neural netwo... [more] | CCS2022-54 pp.57-60 |
| DC, SS | 2022-10-25 14:15 |
Fukushima | (Primary: On-site, Secondary: Online) |
Relationship between the Defects in Learning Programs and the Model Distortion on the Convolutional Neural Networks Takumi Tsuchiya, Kozo Okano, Shinpei Ogata (Shinshu Univ.), Shin Nakajima (NII) SS2022-26 DC2022-32 |
In recent years, the quality issue of machine learning software has become an important concern. When considering the qu... [more] | SS2022-26 DC2022-32 pp.23-28 |
| DC, SS | 2022-10-25 14:40 |
Fukushima | (Primary: On-site, Secondary: Online) |
Comparison of the Coverage Indicators of Evaluation Data for the Convolutional Neural Networks Yuto Yokoyama, Kozo Okano, Shinpei Ogata (Shinshu Univ.), Shin Nakazima (NII) SS2022-27 DC2022-33 |
Neuron Coverage (NC) was proposed as a measure to quantify the usefulness of evaluation data against Deep Neural Network... [more] | SS2022-27 DC2022-33 pp.29-34 |
| PRMU | 2022-10-21 15:40 |
Tokyo | Miraikan - The National Museum of Emerging Science and Innovation (Primary: On-site, Secondary: Online) |
Action Recognition of Anime Ayako Sakuma, Naoshi Kaneko, Kazuhiko Sumi (Aoyama Gakuin Univ.) PRMU2022-28 |
This paper presents an action recognition method for anime characters. Since existing action recognition datasets focus... [more] |
PRMU2022-28 pp.35-40 |
| PRMU | 2022-10-21 16:25 |
Tokyo | Miraikan - The National Museum of Emerging Science and Innovation (Primary: On-site, Secondary: Online) |
Heart Detection Method in Non-Contrast Chest CT Image and Application to Calcium Scoring Yuki Sugimoto, Tetsuya Asakawa (TUT), Kazuki Shimizu, Takuyuki Komoda (THC), Masaki Aono (TUT) PRMU2022-31 |
Coronary artery disease, one of the major causes of death in Japan, is said to be related to coronary artery calcificati... [more] | PRMU2022-31 pp.50-55 |
| AP | 2022-10-20 14:00 |
Gifu | GIFU CITY CULTURE CENTER (Primary: On-site, Secondary: Online) |
A Study on Rain Attenuation Prediction Method by Deep Learning 2
-- Error Characteristics -- Yuji Komatsuya, Tetsuro Imai (TDU), Miyuki Hirose (Kyutech) AP2022-141 |
Recently, the frequency used in wireless systems has got higher significantly, such as B5G (6G), HAPS, etc., and the imp... [more] | AP2022-141 pp.211-215 |
| HIP | 2022-10-18 10:50 |
Kyoto | Kyoto Terrsa (Primary: On-site, Secondary: Online) |
Examination of facial attractiveness features using geometric morphological analysis of and deep learning methods. Takanori Sano, Hideaki Kawabata (Keio Univ.) HIP2022-52 |
In psychology, various studies have been conducted on the features that constitute facial attractiveness. In recent year... [more] | HIP2022-52 pp.26-31 |
| PRMU | 2022-09-14 10:30 |
Kanagawa | (Primary: On-site, Secondary: Online) |
Performance Evaluation of Data Augmentation Using Face Parsing for Improving Face Recognition Hiroya Kawai, Koichi Ito (Tohoku Univ.), Hwann-Tzong Chen (NHTU), Takafumi Aoki (Tohoku Univ.) PRMU2022-12 |
Face recognition is one of the most promising methods to recognize individuals. Since the recognition accuracy is degrad... [more] | PRMU2022-12 pp.13-18 |
| ITE-ME, EMM, IE, LOIS, IEE-CMN, IPSJ-AVM [detail] | 2022-09-13 15:30 |
Online | Keio Univ. Yagami Campus (Hybrid) (Primary: Online, Secondary: On-site) |
The efficient AI System for Rating Facial Expressions for the purpose of Predicting Drivers Sleepiness Tomoya Kubo (Okayama Prefectural Univ. Graduate School), Tomoyuki Yokogawa, Masaki Hokari, Kazutami Arimoto (Okayama Prefectural Univ.), Isao Kayano (Kawasaki Univ. of Medical Welfare), Kagehisa Kajiwara (MURAKAMI CORPORATION) LOIS2022-13 IE2022-35 EMM2022-41 |
In a driver monitoring system, a 3D convolutional neural network (3D CNN) has been used as a neural network (NN) to eval... [more] | LOIS2022-13 IE2022-35 EMM2022-41 pp.19-24 |
| IN, CCS (Joint) |
2022-08-04 10:20 |
Hokkaido | Hokkaido University(Centennial Hall) (Primary: On-site, Secondary: Online) |
Consideration of the structure of CNN models with high image classification performanc Mizuki Dai, Kenya Jinno (Tokyo City University) CCS2022-27 |
In recent years, Transformer-based models such as ViT have shown remarkable performance in image recognition using Deep ... [more] | CCS2022-27 pp.6-9 |
| AP, SANE, SAT (Joint) |
2022-07-27 09:25 |
Hokkaido | Asahikawa Taisetsu Crystal Hall (Primary: On-site, Secondary: Online) |
[Invited Lecture]
A Study of Rain Attenuation Prediction Method by Deep Learning Yuji Komatsuya, Tetsuro Imai (TDU), Miyuki Hirose (Kyutech) AP2022-34 |
Recently, the frequency used in wireless systems has got higher significantly, such as B5G, HAPS, etc., and the importan... [more] | AP2022-34 pp.1-5 |
| CS | 2022-07-15 14:20 |
Kagoshima | Yakushima Environmental and Cultural Village Center (Primary: On-site, Secondary: Online) |
[Invited Talk]
Application of state-space models to CNN estimation methods for indoor location estimation Kaishin Hori, Satoru Aikawa, Sinichiro Yamamoto (Univ. of Hyogo) CS2022-36 |
Currently, GNSS is the most accurate outdoor location estimation technique. On the other hand, the accuracy of GNSS loca... [more] | CS2022-36 pp.100-103 |
| AI | 2022-07-04 15:20 |
Hokkaido | (Primary: On-site, Secondary: Online) |
Face image generation with audio information using deep learning Kotaro Koseki, Yuichi Sei, Yasuyuki Tahara, Akihiko Ohsuga (UEC) AI2022-12 |
(To be available after the conference date) [more] | AI2022-12 pp.60-65 |
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