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All Technical Committee Conferences (Searched in: All Years)
| Committee | Date Time | Place | Paper Title / Authors | Abstract | Paper # | |
| RCC, ITS, WBS | 2022-12-14 11:05 |
Shiga | Ritsumeikan Univ. BKC (Primary: On-site, Secondary: Online) |
Vehicle Route Detection Network Using Continuous Roadside Units Gunhee Cho, Tao Yu, Jin Nakazato, Kei Sakaguchi (TokyoTech)  WBS2022-55 ITS2022-31 RCC2022-55 |
For the purpose of establishing a digital twin society, this paper proposes an object recognition network architecture u... [more] | WBS2022-55 ITS2022-31 RCC2022-55 pp.114-119 |
| CS, IE, IPSJ-AVM, ITE-BCT [detail] | 2022-11-25 11:30 |
Aichi | Nagoya Institute of Technology (Primary: On-site, Secondary: Online) |
Privacy-Preserving Facial Identification using Lensless Imaging Kohsuke Yamamura, Yoshihiro Maeda (TUS), Daisuke Sugimura (Tsuda Univ.), Takayuki Hamamoto (TUS) CS2022-59 IE2022-47 |
Lensless imaging is a method of obtaining optically encoded images without using a lens.In this imaging method, reconstr... [more] | CS2022-59 IE2022-47 pp.63-66 |
| 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 11:00 |
Tokyo | (Primary: On-site, Secondary: Online) |
An Image Recognition Model of Danger Objects for Diverse Clients using Federated Learning Yasuhiro Nitta, Ryo Yonetani, Maki Sugimoto, Hideo Saito (Keio Univ.) MVE2022-15 |
A disabled person can have cognition of danger objects during walking, which might not coincide with a non-disabled pers... [more] | MVE2022-15 pp.26-31 |
| ICD, SDM, ITE-IST [detail] | 2022-08-10 15:15 |
Online | [Invited Talk]
A CMOS Image Sensor and an AI Accelerator for Realizing Edge-Computing-Based Surveillance Camera Systems Fukashi Morishita, Norihito Kato, Satoshi Okubo, Takao Toi, Mitsuru Hiraki, Sugako Otani, Hideaki Abe, Yuji Shinohara, Hiroyuki Kondo (Renesas Electronics) SDM2022-52 ICD2022-20 |
This paper presents a CMOS image sensor and an AI accelerator to realize surveillance camera systems based on edge compu... [more] | SDM2022-52 ICD2022-20 pp.83-86 |
|
| ICD, SDM, ITE-IST [detail] | 2022-08-10 16:00 |
Online | IC with Integrated Imager and Ultra-Low Latency All-Digital In-Imager 2D Binary Convolutional Neural Network Accelerator for Image Classification Ruizhi Wang, Cheng-Hsuan Wu, Makoto Takamiya (The Univ. of Tokyo) SDM2022-53 ICD2022-21 |
In the field of real-time image recognition, the computing latency of convolutional neural network become an issue. In t... [more] | SDM2022-53 ICD2022-21 pp.87-92 |
|
| 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 |
| CCS, NLP | 2022-06-09 15:20 |
Osaka | (Primary: On-site, Secondary: Online) |
Speeding-up by Reduction of Processing Paths in Octave Convolution Akito Yoshikawa, Hidehiro Nakano (Tokyo City Univ.) NLP2022-6 CCS2022-6 |
Octave Convolution (OctConv), one of the convolutional neural network methods, can also improve accuracy while reducing ... [more] | NLP2022-6 CCS2022-6 pp.27-30 |
| IMQ | 2022-05-27 14:00 |
Tokyo | Animal Video Retrieval System Using Image Recognition Chinatsu Watanabe (Kogakuin Univ.), Mayu Kaneko (Mizuho Research & Technologies), Atsumu Harada, Naiwala P. Chandrasiri (Kogakuin Univ.) IMQ2022-2 |
In general, the search function in a video sharing service site evaluates the relevance of a search query to the title, ... [more] | IMQ2022-2 pp.7-11 |
|
| SC | 2022-05-27 09:55 |
Online | Online | Considerations for Identifying Machine Learning Models Naoto Kiribuchi, Ryohei Suzuki, Nami Ashizawa (NTT), Tetsushi Ohki, Hiroshi Mineno, Masakatsu Nishigaki (Shizuoka Univ.) SC2022-2 |
As a part of considerations for identifying machine learning models, we experimented whether we can identify multiple di... [more] | SC2022-2 pp.7-12 |
| 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 |
| SIP, BioX, IE, MI, ITE-IST, ITE-ME [detail] | 2022-05-20 16:40 |
Kumamoto | Kumamoto University Kurokami Campus (Primary: On-site, Secondary: Online) |
3D Medical Image Segmentation Using 2.5D Deformable Convolutional CNN Yuya Okumura, Kudo Hiroyuki, Takizawa Hotaka (Tsukuba Univ.) SIP2022-29 BioX2022-29 IE2022-29 MI2022-29 |
An effective method to improve the accuracy of 3D medical image segmentation using deep learning is to use deformable co... [more] | SIP2022-29 BioX2022-29 IE2022-29 MI2022-29 pp.150-155 |
| CQ, IMQ, MVE, IE (Joint) [detail] |
2022-03-10 15:50 |
Online | Online (Zoom) | Player Tracking Using Uniform Number Constraints in Basketball Videos Takuya Okamoto, Yasuhiko Kitamura (Kwansei Gakuin Univ.) IMQ2021-32 IE2021-94 MVE2021-61 |
We can track multiple players from basketball game videos using image recognition and Multi Object Tracking technologie... [more] | IMQ2021-32 IE2021-94 MVE2021-61 pp.115-120 |
| WIT, IPSJ-AAC | 2022-03-08 10:20 |
Online | Online | The Prototype of a Real Time Mobile Braille Pattern Detection Utilizing Machine Learning for a Self-study Tool for Visually Impaired People Jevri Tri Ardiansah, Okazaki Yasuhisa (Saga University) WIT2021-45 |
The capacity to read and write is called literacy. Literacy is necessary for a good education, a good job, and a high qu... [more] | WIT2021-45 pp.12-17 |
| WIT, IPSJ-AAC | 2022-03-09 15:40 |
Online | Online | Development of meal support system for the visually impaired based on food recognition using image analysis Rei Sasaki, Hirokazu Seki (CIT) WIT2021-59 |
The purpose of this study is to develop a system to assist the visually impaired to eat alone. We devised an image analy... [more] | WIT2021-59 pp.92-96 |
| NLC | 2022-03-07 11:05 |
Online | Online | Sightseeing spot detection and automatic generation of explanations using Flickr Hanami Ookada (Hiroshima City Univ.), Aya Ishino (HUE), Toshiyuki Takezawa (Hiroshima City Univ.) NLC2021-30 |
Using travel photos with latitude and longitude information in Flickr and image recognition technology, we conducted a s... [more] | NLC2021-30 pp.13-18 |
| MICT, EMCJ (Joint) |
2022-03-04 10:05 |
Online | Online | A study on silent word recognition using various sensors Masaya Kusamoto, Kenko Ota (NIT) MICT2021-104 |
The aim of this study is to clarify the effectiveness of silent word recognition using multiple sensors. When a visible ... [more] | MICT2021-104 pp.19-24 |
| MBE, NC (Joint) |
2022-03-02 09:30 |
Online | Online | A Study on Improvement of Recognition Accuracy and Speed-up of SOM-based Classification System Shun Tasaka, Hiroomi Hikawa (Kansai Univ.) NC2021-46 |
This paper discusses a new type of image classifier called class-SOM, which is based on self-organizing map (SOM). The... [more] |
NC2021-46 pp.1-4 |
| RCS, SR, SRW (Joint) |
2022-03-04 16:40 |
Online | Online | Denoising Method Using Deep Image Prior for Improving Accuracy of Radar Target Detection Koji Endo, Kohei Yamamoto, Tomoaki Ohtsuki (Keio Univ.) RCS2021-299 |
A Multiple-Input Multiple-Output (MIMO) Frequency-Modulated Continuous Wave (FMCW) radar can provide various application... [more] | RCS2021-299 pp.241-246 |
| IE, ITS, ITE-AIT, ITE-ME, ITE-MMS [detail] | 2022-02-22 11:10 |
Online | Online | Enhancing Personalized Food Image Classifier by Visual Attention and Class-Dependent Weighting Seum Kim, Yoko Yamakata, Kiyoharu Aizawa (UTokyo) ITS2021-47 IE2021-56 |
In a real-world setting, food records are very noisy and strongly imbalanced. Besides, inter-class similarity and intra-... [more] | ITS2021-47 IE2021-56 pp.133-138 |
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