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All Technical Committee Conferences (Searched in: All Years)
| Committee | Date Time | Place | Paper Title / Authors | Abstract | Paper # | |
| IT, EMM | 2022-05-17 13:25 |
Gifu | Gifu University (Primary: On-site, Secondary: Online) |
A Note on Time-Varying Two-Dimensional Autoregressive Models and the Bayes Codes Yuta Nakahara, Toshiyasu Matsushima (Waseda Univ.)  IT2022-2 EMM2022-2 |
This paper proposes a two-dimensional autoregressive model with time-varying parameters as a stochastic model for explai... [more] | IT2022-2 EMM2022-2 pp.7-12 |
| IE, ITS, ITE-AIT, ITE-ME, ITE-MMS [detail] | 2022-02-21 15:35 |
Online | Online | Effects of foreground and unequal shielding on depth perception Nobutaka Natsui, Hisaki Nate, Kazuo Ishikawa (Tokyo Polytechnic Univ.) |
When observing binocular stereoscopic images using HMDs, problems such as unnaturalness and discomfort in stereoscopic p... [more] | |
| IE, ITS, ITE-AIT, ITE-ME, ITE-MMS [detail] | 2022-02-21 13:15 |
Online | Online | Towards Universal Deep Image Compression Koki Tsubota (UTokyo), Hiroaki Akutsu (Hitachi), Kiyoharu Aizawa (UTokyo) ITS2021-31 IE2021-40 |
In this paper, we investigate deep image compression towards universal usage. In image compression, it is desirable to b... [more] | ITS2021-31 IE2021-40 pp.37-42 |
| OCS, CS (Joint) |
2022-01-13 14:30 |
Yamaguchi | Conference room 204A・B at KDDI Ishin-hall (Primary: On-site, Secondary: Online) |
Image Compression and Progressive Retransmission Scheme on Edge Computing System for Image Data Reduction Mutsuki Nakahara, Daisuke Hisano (Osaka Univ.), Mai Nishimura (OSX), Takayuki Nishio (Tokyo Tech.), Yoshitaka Ushiku (OSX), Kazuki Maruta (Tokyo Tech.), Yu Nakayama (Tokyo Univ. of Agriculture and Tech.) CS2021-69 |
Edge computing has been getting attention due to reducing the data traffic in the backbone network. On the other hand, t... [more] | CS2021-69 pp.7-12 |
| HIP | 2021-10-22 14:25 |
Online | Online | Visually Fidelitous Dynamic-Range Compression from HDR Images
-- Dependency of Individual on Perceived Time by Observing Images Reproduced with Global Tone Mapping Curves -- Yuichiro Orrita, Genta Higashi, Shoko Hira, Masayuki Kashima (Kagosima Univ.), Sakuichi Ohtsuka (International College of Technology, Kanazawa) HIP2021-46 |
Three different Global-tone-mapping (i.e., CD, SN, and DR) were employed for reproducing SDR images for subjective evalu... [more] | HIP2021-46 pp.87-92 |
| EMM, IT | 2021-05-21 13:10 |
Online | Online | A Study of Detecting Adversarial Examples Using Sensitivities to Multiple Auto Encoders Yuma Yamasaki, Minoru Kuribayashi, Nobuo Funabiki (Okayama Univ.), Huy Hong Nguyen, Isao Echizen (NII) IT2021-11 EMM2021-11 |
By removing the small perturbations involved in adversarial examples, the image classification result returns to the cor... [more] | IT2021-11 EMM2021-11 pp.60-65 |
| EMM, IT | 2021-05-21 14:25 |
Online | Online | A reversible data hiding method with high flexibility in compressive encrypted images Ryota Motomura, Shoko Imaizumi (Chiba Univ.), Hitoshi Kiya (Tokyo Metropolitan Univ.) IT2021-14 EMM2021-14 |
In this paper, we propose a reversible data hiding method in encrypted images, where both the com-pression efficiency an... [more] | IT2021-14 EMM2021-14 pp.78-83 |
| SeMI, IPSJ-MBL, IPSJ-UBI [detail] | 2021-03-02 10:00 |
Online | Online | Traffic Reduction Method on Wireless Edge Computing by Retransmission Control Based on Image Recognition Accuracy Mutsuki Nakahara, Daisuke Hisano (Osaka Univ.), Mai Nishimura, Yoshitaka Ushiku (OSX), Kazuki Maruta (TIT), Yu Nakayama (TUAT) SeMI2020-62 |
In this paper, we propose a retransmission control system based on image recognition accuracy as a traffic reduction met... [more] | SeMI2020-62 pp.23-28 |
| IE | 2021-01-21 16:40 |
Online | Online | [Invited Talk]
Advanced visual media fall in love with light field representation rather than conventional image processing
-- With COVID-19, Beyond COVID-19 -- Kazuya Kodama (NII) IE2020-40 |
Nowadays we enjoy visual media based on technologies for image acquisition, compression, processing, transmission and di... [more] | IE2020-40 pp.19-20 |
| SIP, IT, RCS | 2021-01-22 15:15 |
Online | Online | An Image Generative Model with Various Auto-regressive Coefficients Depending on Neighboring Pixels and the Bayes Code for It Masahiro Takano, Yuta Nakahara, Toshiyasu Matsushima (Waseda Univ.) IT2020-108 SIP2020-86 RCS2020-199 |
In this papar, we propose an expanded model of an autoregressive stochastic generative model for images. This model cont... [more] | IT2020-108 SIP2020-86 RCS2020-199 pp.253-258 |
| SIS, ITE-BCT | 2020-10-01 13:20 |
Online | Online | Robustness Evaluation of Detectinon methods for Image manipulation with GANs Miki Tanaka, Hitoshi Kiya (Tokyo Metropolitan Univ.) SIS2020-14 |
Recent rapid advances in image manipulation tools and deep image synthesis techniques, such as Generative Adversarial Ne... [more] | SIS2020-14 pp.23-28 |
| IT, EMM | 2020-05-28 15:25 |
Online | Online | An Autoregressive Image Generative Model and the Bayes Code for It Yuta Nakahara, Toshiyasu Matsushima (Waseda Univ.) IT2020-4 EMM2020-4 |
In this paper, we propose an autoregressive stochastic generative model for images. This model should be one of the mos... [more] |
IT2020-4 EMM2020-4 pp.19-24 |
| PRMU, IPSJ-CVIM | 2020-03-16 16:45 |
Kyoto | (Cancelled but technical report was issued) |
Image compression by colorization Hiya Roy, Subhajit Chaudhury, Toshihiko Yamasaki, Tatsuaki Hashimoto (UTokyo) PRMU2019-86 |
Image compression techniques exploit the inherent psycho-visual limitations in human vision to reduce the number of bits... [more] | PRMU2019-86 pp.107-108 |
| IE, IMQ, MVE, CQ (Joint) [detail] |
2020-03-06 14:50 |
Fukuoka | Kyushu Institute of Technology (Cancelled but technical report was issued) |
A high-compression video coding method for video analysis using Deep Learning Tomonori Kubota, Takanori Nakao, Eiji Yoshida (Fujitsu Lab.) IMQ2019-39 IE2019-121 MVE2019-60 |
In this paper, we propose a high-compression video coding method for video analysis using Deep Learning. The method anal... [more] | IMQ2019-39 IE2019-121 MVE2019-60 pp.121-126 |
| EMM | 2020-03-05 14:25 |
Okinawa | (Cancelled but technical report was issued) |
[Poster Presentation]
Extended EtC images for flexible data hiding and extracting Ryoichi Hirasawa, Shoko Imaizumi (Chiba Univ.), Hitoshi Kiya (Tokyo Metropolitan Univ.) EMM2019-109 |
This paper proposes a data hiding method for encrypted images by using an encryption-then-compression (EtC) system. Afte... [more] | EMM2019-109 pp.43-48 |
| EMM | 2020-03-05 16:45 |
Okinawa | (Cancelled but technical report was issued) |
[Poster Presentation]
Detecting Adversarial Examples Based on Sensitivities to Lossy Compression Algorithms Akinori Higashi, Minoru Kuribayashi, Nobuo Funabiki (Okayama Univ.), Huy Hong Nguyen, Isao Echizen (NII) EMM2019-123 |
The adversarial examples are created by adding small perturbations to an input image for misleading an CNN-based image c... [more] | EMM2019-123 pp.113-116 |
| ITE-HI, IE, ITS, ITE-MMS, ITE-ME, ITE-AIT [detail] | 2020-02-27 16:50 |
Hokkaido | Hokkaido Univ. (Cancelled but technical report was issued) |
Depth perception when a stereoscopic target is occluded on both sides or one side by the foreground Nobutaka Natsui, Hisaki Nate, Kazuo Isikawa (Tokyo Polytechnic Univ.) |
When we shoot and observe binocular stereoscopic images, problems such as unnatural stereoscopic effects and strangeness... [more] | |
| NLP, NC (Joint) |
2020-01-24 11:10 |
Okinawa | Miyakojima Marine Terminal | Proposal of Compression Method for Planetary Surface Image using Sparse Coding Yoshifumi Uesaka, Hayaru Shouno (UEC) NC2019-65 |
In recent years, the demand for space development has been increasing. We treat an efficient image transmitting system f... [more] | NC2019-65 pp.33-38 |
| SIS | 2019-12-12 15:15 |
Okayama | Okayama University of Science | A Reversible Data Hiding Method for Both Plain and Encrypted Images Yusuke Izawa, Ryoichi Hirasawa, Shoko Imaizumi (Chiba Univ.), Hitoshi Kiya (TMU) SIS2019-28 |
In this paper, we propose a reversible data hiding method, where the data embedded into the original image can be extrac... [more] | SIS2019-28 pp.29-34 |
| EA | 2019-12-12 14:00 |
Fukuoka | Kyushu Inst. Tech. | Removal of musical noise using deep learning without pre-training Takuya Fujimura, Ryoichi Miyazaki (NITTC) EA2019-69 |
In this paper, we propose the musical noise elimination using the deep learning which does not require pre-training. It ... [more] | EA2019-69 pp.23-29 |
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