Committee |
Date Time |
Place |
Paper Title / Authors |
Abstract |
Paper # |
SIP, SP, EA, IPSJ-SLP [detail] |
2024-02-29 17:20 |
Okinawa |
(Primary: On-site, Secondary: Online) |
An Enhanced Privacy-Preserving Scheme for Federated Learning of Vision Transformer without Model Performance Degradation Rei Aso, Sayaka Shiota, Hitoshi Kiya (Tokyo Metropolitan Univ.) EA2023-80 SIP2023-127 SP2023-62 |
Federated learning is a learning method for training models over multiple participants without directly sharing their ra... [more] |
EA2023-80 SIP2023-127 SP2023-62 pp.115-120 |
ITS, IE, ITE-MMS, ITE-ME, ITE-AIT [detail] |
2024-02-20 14:00 |
Hokkaido |
Hokkaido Univ. |
Fine-tuning Model for Diagnosis of Autism Spectrum Disorder Using fMRI Data Sae Yoshihara, Takuya Kitamura (NITT) ITS2023-71 IE2023-60 |
In this paper, we propose and evaluate novel classification models generated by fine-tuning a pre-trained image classifi... [more] |
ITS2023-71 IE2023-60 pp.135-140 |
PRMU, MVE, VRSJ-SIG-MR, IPSJ-CVIM |
2024-01-26 15:58 |
Kanagawa |
Keio Univ. (Hiyoshi Campus) |
Tomohiro Hayase (CMVL), Sacha Braun (L'X), Itsuki Orito (Cluster) PRMU2023-50 |
(To be available after the conference date) [more] |
PRMU2023-50 pp.56-61 |
SIP |
2023-08-07 12:50 |
Osaka |
Osaka Univ. (Suita) Convention Center (Primary: On-site, Secondary: Online) |
An Extension of Image Encryption for Vision Transformer Considering Privacy Protection Haiwei Lin, Shoko Imaizumi (Chiba Univ.), Kiya Hitoshi (Tokyo Metropolitan Univ) SIP2023-46 |
In this paper, we propose an extended framework of access control for Vision Transformer (ViT).
The previous study acc... [more] |
SIP2023-46 pp.1-6 |
SIP |
2023-08-07 13:10 |
Osaka |
Osaka Univ. (Suita) Convention Center (Primary: On-site, Secondary: Online) |
A Perceptual Collation Method for Color Halftone Images Using Vision Transformer Daiki Fujikawa, Shoko Imaizumi, Takahiko Horiuchi (Chiba Univ.) SIP2023-47 |
We propose an automatic collation method based on human perception in this paper.
The collation target of the propose... [more] |
SIP2023-47 pp.7-12 |
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 |
WIT, IPSJ-AAC |
2023-03-23 09:40 |
Online |
Online |
Mouth shape recognition for speech scene of patients with intractable neurological diseases Yuki Gondo, Yuya Nakamura, Takeshi Saitoh (kyutech), Kazuyuki Itoh (NRCPD) WIT2022-24 |
We are working on mouth shape recognition, which is the basic technology for the development of mouth-shape character me... [more] |
WIT2022-24 pp.27-31 |
IMQ, IE, MVE, CQ (Joint) [detail] |
2023-03-17 15:40 |
Okinawa |
Okinawaken Seinenkaikan (Naha-shi) (Primary: On-site, Secondary: Online) |
Improvement of cross-attention modules for image captioning using pixel-wise semantic information Zhihao Chen, Keisuke Doman, Yoshito Mekada (Chukyo Univ.) IMQ2022-84 IE2022-161 MVE2022-114 |
Most of image captioning models have attention modules, and the module outputs an attention map (weighted feature map) f... [more] |
IMQ2022-84 IE2022-161 MVE2022-114 pp.333-338 |
PRMU, IBISML, IPSJ-CVIM [detail] |
2023-03-02 11:05 |
Hokkaido |
Future University Hakodate (Primary: On-site, Secondary: Online) |
On the Effectiveness of Formula-Driven Supervised Learning for Medical Image Tasks Ryuto Endo, Shuya Takahashi, Eisaku Maeda (TDU) PRMU2022-71 IBISML2022-78 |
Deep learning for image information processing often uses manually maintained natural image data. However, these data ha... [more] |
PRMU2022-71 IBISML2022-78 pp.71-75 |
PRMU, IBISML, IPSJ-CVIM [detail] |
2023-03-02 11:25 |
Hokkaido |
Future University Hakodate (Primary: On-site, Secondary: Online) |
Binarization of Vision Transformer with Scaling Factors Shun Sato, Shun Sawada, Hidefumi Ohmura, Kouichi katsurada (TUS) PRMU2022-83 IBISML2022-90 |
1bit neural network optimization is an optimization technique that achieves a significant increase in computational spee... [more] |
PRMU2022-83 IBISML2022-90 pp.134-139 |
PRMU, IBISML, IPSJ-CVIM [detail] |
2023-03-02 17:00 |
Hokkaido |
Future University Hakodate (Primary: On-site, Secondary: Online) |
Evaluation of Spatial Transformer Network with Vision Transformer Yoshiharu Iwasaki (Ritsumeikan Univ.), Yu Wang (Hitotsubashi Univ.), Jien Kato (Ritsumeikan Univ.) PRMU2022-91 IBISML2022-98 |
Spatial Transformer is a module that performs spatial transformation of input images or the feature maps. In our researc... [more] |
PRMU2022-91 IBISML2022-98 pp.163-168 |
EMM |
2023-03-02 13:00 |
Nagasaki |
Fukue culture hall (Primary: On-site, Secondary: Online) |
[Poster Presentation]
Influence of Data Hiding for Transformer Encoder of ViT Using DM-QIM Shuntaro Fukuoka, Shoko Imaizumi (Chiba Univ.) EMM2022-68 |
In this paper, we evaluate the influence of data hiding for vision transformer (ViT) models. Specifically, we embed a pa... [more] |
EMM2022-68 pp.7-12 |
PRMU, IBISML, IPSJ-CVIM [detail] |
2023-03-03 16:20 |
Hokkaido |
Future University Hakodate (Primary: On-site, Secondary: Online) |
Collaborative Intelligence for Transformer-Based AI Systems Monikka Roslianna Busto, Shohei Enomoto, Takeharu Eda (NTT SIC) PRMU2022-111 IBISML2022-118 |
[more] |
PRMU2022-111 IBISML2022-118 pp.275-280 |
IE, ITS, ITE-MMS, ITE-ME, ITE-AIT [detail] |
2023-02-21 10:30 |
Hokkaido |
Hokkaido Univ. |
A Note on Traffic Sign Recognition Based on Vision Transformer Adapter Using Visual Feature Matching Yaozong Gan, Guang Li, Ren Togo, Keisuke Maeda, Takahiro Ogawa, Miki Haseyama (Hokkaido Univ.) |
Traffic sign recognition is a real-world task that involves many constraints and complications. Traffic sign recognition... [more] |
|
NC, NLP |
2023-01-29 15:05 |
Hokkaido |
Future University Hakodate (Primary: On-site, Secondary: Online) |
Predictions and Attentions Acquired by Vision Transformer with Source-Target Attention from Dilated Convolutions on Small Data Sets Tatsuki Shimura, Katsumi Tadamura, Toshikazu Samura (Yamaguchi Univ) NLP2022-104 NC2022-88 |
Vision Transformer (ViT) requires large data sets during pre-training phase to acquire high classification accuracy on a... [more] |
NLP2022-104 NC2022-88 pp.123-128 |
EMM |
2023-01-26 09:30 |
Miyagi |
Tohoku Univ. (Primary: On-site, Secondary: Online) |
Influence of Data Hiding in EtC-Image Classification with Vision Transformer Kosuke Abe, Shoko Imaizumi (Chiba Univ.), Hitoshi Kiya (Tokyo Metropolitan Univ.) EMM2022-61 |
A privacy-preserving image classification method with the vision transformer (ViT) was proposed in which the accuracy of... [more] |
EMM2022-61 pp.1-6 |
SANE |
2022-12-16 14:15 |
Nagasaki |
Nagasaki Public Hall (Primary: On-site, Secondary: Online) |
Land Cover Classification for Polarimetric SAR Images Based on Vision Transformer Hongmiao Wang, Danwei Lu (Tsinghua Univ.), Junjun Yin (USTB), Jian Yang (Tsinghua Univ.) SANE2022-83 |
Deep learning methods have been widely studied for polarimetric synthetic aperture radar (PolSAR) land cover classificat... [more] |
SANE2022-83 pp.100-104 |
PRMU |
2022-12-16 15:10 |
Toyama |
Toyama International Conference Center (Primary: On-site, Secondary: Online) |
[Short Paper]
Cosine Similarity Based Attention on a Hypersphere for Vision Transformers Jungdae Lee, Rei Kawakami, Nakamasa Inoue (Tokyo Tech) PRMU2022-52 |
The success of Vision Transformers in computer vision is usually attributed to its distinct structure of self-attention ... [more] |
PRMU2022-52 pp.106-109 |
CAS, SIP, VLD, MSS |
2022-06-16 15:05 |
Aomori |
Hachinohe Institute of Technology (Primary: On-site, Secondary: Online) |
Image Classification Using Vision Transformer for Compressible Encrypted Images Genki Hamano, Shoko Imaizumi (Chiba Univ.), Hitoshi Kiya (Tokyo Metropolitan Univ.) CAS2022-8 VLD2022-8 SIP2022-39 MSS2022-8 |
In this paper, we propose an image classification method for compressible encrypted images without losing classification... [more] |
CAS2022-8 VLD2022-8 SIP2022-39 MSS2022-8 pp.40-45 |
PRMU, IPSJ-CVIM |
2022-03-10 09:30 |
Online |
Online |
PRMU2021-62 |
no English abstract [more] |
PRMU2021-62 pp.13-18 |