Committee |
Date Time |
Place |
Paper Title / Authors |
Abstract |
Paper # |
NLP, CCS |
2024-06-06 16:45 |
Fukuoka |
West Japan General Exhibition Center AIM |
Hierarchical lossless depth image compression based on depth map colorization by cellular neural networks Tasuku Kuroda, Seiya Kushi, Shungo Saizuka (Chukyo Univ), Tsuyoshi Otake (Tamagawa Univ), Hisashi Aomori (Chukyo Univ) NLP2024-27 CCS2024-14 |
The widespread of compact and inexpensive RGB-D sensors has recently led to the increased utilization of RGB-D images in... [more] |
NLP2024-27 CCS2024-14 pp.57-60 |
IT, EMM |
2024-05-30 16:00 |
Chiba |
Chiba University (Nishi-Chiba Campus) |
Asymmetric encoding-decoding schemes for first-order Markov sources Hirosuke Yamamoto (U. of Tokyo), Ken-ichi Iwata (U.of Fukui) IT2024-5 EMM2024-5 |
Last year we proposed an Asymmetric Encoding--Decoding Scheme (AEDS), in which a data sequence $s^T=s_1s_2 ¥cdots s_T$ i... [more] |
IT2024-5 EMM2024-5 pp.19-24 |
NLP |
2024-05-10 11:20 |
Kagawa |
Kagawa Prefecture Social Welfare Center |
Lossless Color Image Compression Based on Colorization by Cellular Neural Networks Shungo Saizuka, Seiya Kushi, Tasuku Kuroda (Chukyo Univ.), Tsuyoshi Otake (Tamagawa Univ.), Hisashi Aomori (Chukyo Univ.) NLP2024-13 |
Colorization is the process that restores colors on a grayscale image.
Recently, various colorization-based encoding me... [more] |
NLP2024-13 pp.63-67 |
NC, MBE, NLP, MICT (Joint) [detail] |
2024-01-24 10:00 |
Tokushima |
Naruto University of Education |
Hierarchical lossless compression of high dynamic range images using predictors based on cellular neural networks Seiya Kushi, Kazuki Nakashima, Hideharu Toda (Chukyo Univ.), Tsuyoshi Otake (Tamagawa Univ.), Hisashi Aomori (Chukyo Univ.) NLP2023-85 MICT2023-40 MBE2023-31 |
We have been developing a scalable lossless coding method using cellular neural networks (CNN) as predictors. This metho... [more] |
NLP2023-85 MICT2023-40 MBE2023-31 pp.12-15 |
BioX, SIP, IE, ITE-IST, ITE-ME [detail] |
2023-05-18 15:15 |
Mie |
Sansui Hall, Mie University (Primary: On-site, Secondary: Online) |
SIP2023-5 BioX2023-5 IE2023-5 |
Compressing video and images with lossy compression degrades input data.Therefore, image quality evaluation is necessary... [more] |
SIP2023-5 BioX2023-5 IE2023-5 pp.16-21 |
EMM |
2023-03-02 13:00 |
Nagasaki |
Fukue culture hall (Primary: On-site, Secondary: Online) |
[Poster Presentation]
An extension of reversible data hiding in encrypted images with high compression performance and flexible processing order Eichi Arai, Shoko Imaizumi (Chiba Univ.) EMM2022-67 |
In this paper, we propose a reversible data hiding in encrypted images (RDH-EI) method that achieves both a high compres... [more] |
EMM2022-67 pp.1-6 |
IE, ITS, ITE-MMS, ITE-ME, ITE-AIT [detail] |
2023-02-21 11:10 |
Hokkaido |
Hokkaido Univ. |
[Special Talk]
Study of Probability Modeling for Lossless Image Coding Using Example Search and Adaptive Prediction Hiroki Kojima (KDDI), Yasuyo Kita, Ichiro Matsuda (Tokyo Univ. of Science) ITS2022-46 IE2022-63 |
Many efficient lossless image coding methods predict the next pel value to be coded from the pels already coded, and rem... [more] |
ITS2022-46 IE2022-63 p.25 |
CAS, NLP |
2022-10-20 14:55 |
Niigata |
(Primary: On-site, Secondary: Online) |
Hierarchical Lossless Coding with Arithmetic Coders for Each CNN Predictor Kazuki Nakashima, Ryo Nakazawa, Hideharu Toda, Hisashi Aomori (Chukyo Univ.), Tsuyoshi Otake (Tamagawa Univ.), Ichiro Matsuda, Susumu Itoh (TUS) CAS2022-23 NLP2022-43 |
We have been developing a scalable lossless coding method using the cellular neural networks (CNN) as predictors.
This ... [more] |
CAS2022-23 NLP2022-43 pp.20-24 |
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 |
CQ, IMQ, MVE, IE (Joint) [detail] |
2022-03-10 15:00 |
Online |
Online (Zoom) |
[Special Talk]
Lossless Image Coding using Inpainting-Oriented Deep Pixel Predictor Keita Takahashi (Nagoya Univ.) IMQ2021-31 CQ2021-122 IE2021-93 MVE2021-60 |
I will be presenting our previous paper that received IE special Award 2020 to encourage discussions for future directio... [more] |
IMQ2021-31 CQ2021-122 IE2021-93 MVE2021-60 p.114(IMQ), p.124(CQ), p.114(IE), p.114(MVE) |
RCS, SIP, IT |
2022-01-21 10:55 |
Online |
Online |
A lossless audio codec based on hierarchical residual prediction Taiyo Mineo, Shouno Hayaru (UEC) IT2021-71 SIP2021-79 RCS2021-239 |
In this study, we propose a novel lossless audio codec that has precise predictive performance from the neural network a... [more] |
IT2021-71 SIP2021-79 RCS2021-239 pp.239-244 |
COMP |
2021-10-23 13:15 |
Online |
Online |
[Invited Talk]
Optimal-Time Queries on BWT-runs Compressed Indexes Takaaki Nishimoto, Yasuo Tabei (RIKEN) COMP2021-16 |
Indexing highly repetitive strings (i.e., strings with many repetitions) for fast queries has become a central research ... [more] |
COMP2021-16 p.19 |
IE, SIP, BioX, ITE-IST, ITE-ME [detail] |
2021-06-03 16:00 |
Online |
Online |
Fast Implementation of the Lossless Image Coding Method Based on Example Search and Probability Model Optimization Hiroki Kojima, Yusuke Kameda, Yasuyo Kita, Ichiro Matsuda, Susumu Itoh (Tokyo Univ of Science.) SIP2021-3 BioX2021-3 IE2021-3 |
We previously proposed a lossless image coding method based on example search and probability model optimization. In the... [more] |
SIP2021-3 BioX2021-3 IE2021-3 pp.10-14 |
IE |
2021-01-21 13:00 |
Online |
Online |
Comparing Pixel Predictors with Different Coding Order for Lossless Image Coding Aki Kunieda, Keita Takahashi, Toshiaki Fujii (Nagoya Univ.) IE2020-34 |
The efficiency of lossless image coding depends on the pixel predictors, with which unknown pixels are predicted from al... [more] |
IE2020-34 pp.1-6 |
IE |
2021-01-21 14:00 |
Online |
Online |
[Invited Talk]
Lossless Image/Video Coding Method Based on Probability Model Estimation and Optimization Kyohei Unno (KDDI Research) IE2020-36 |
In this talk, the lossless image/video coding method that is proposed by the author is introduced. The proposed method e... [more] |
IE2020-36 p.8 |
SIP, IT, RCS |
2021-01-21 15:45 |
Online |
Online |
[Special Invited Talk]
Turbo Equalization to Lossless/Lossy Distributed Multiterminal Source Coding: How are they connected?
-- Towards Distributed Hypothesis Testing over IoT Networks -- Tadashi Matsumoto (JAIST) IT2020-80 SIP2020-58 RCS2020-171 |
A goal of this talk is to provide the audience with the knowledge about how the presenter's research experiences and foo... [more] |
IT2020-80 SIP2020-58 RCS2020-171 p.99 |
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 |
SIP |
2020-08-28 10:30 |
Online |
Online |
Improvement Convergence Rate of the Sign Algorithm by Natural Gradient Method Taiyo Mineo, Hayaru Shouno (UEC) SIP2020-34 |
In lossless audio compression, it is essential to predictive residuals to be sparse, since we apply entropy codings to r... [more] |
SIP2020-34 pp.19-24 |
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 |
ITE-BCT, SIS |
2019-10-25 10:50 |
Fukui |
Fukui International Activities Plaza |
A lossless predictive coding of floating-point data using L1-norm optimization Syusuke Kohara, Shinji Fukuma, Shin-ichiro mori (Univ. FUKUI) SIS2019-20 |
(To be available after the conference date) [more] |
SIS2019-20 pp.73-76 |