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All Technical Committee Conferences (Searched in: All Years)
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Search Results: Conference Papers |
Conference Papers (Available on Advance Programs) (Sort by: Date Descending) |
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Committee |
Date Time |
Place |
Paper Title / Authors |
Abstract |
Paper # |
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 |
NLP |
2023-11-29 10:40 |
Okinawa |
Nago city commerce and industry association |
A Study on General Purpose Data Transmission Scheme Using SD-CNN with Coupled Cells Koki Koase (Chukyo Univ.), Ryoichi Shibata (Aiphon Co.), Hideharu Toda (Chukyo Univ.), Taishi Iriyama (Saitama Univ.), Tsuyoshi Otake (Tamagawa Univ.), Hisashi Aomori (Chukyo Univ.) NLP2023-71 |
The sigma-delta cellular neural network (SD-CNN) is an artificial vision system that mimics the retina of biology. SD-CN... [more] |
NLP2023-71 pp.53-56 |
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 |
NLP |
2018-08-08 15:00 |
Kagawa |
Saiwai-cho Campus, Kagawa Univ. |
Super-Resolution Reconstruction Using Adaptive Nearest Neighbor Interpolation by Iterative Back-Projection Ryuya Ukai, Ryohei Mizutani, Yuki kawai, Teruki Uchida, Hideharu Toda (Chukyo Univ.), Tsuyoshi Otake, Masatoshi Sato (Tamagawa Univ.), Hisashi Aomori (Chukyo Univ.) NLP2018-58 |
The pixel density of display devices are improving, and the importance of the resolution as a criteria to determine the ... [more] |
NLP2018-58 pp.31-34 |
NLP |
2018-08-08 15:25 |
Kagawa |
Saiwai-cho Campus, Kagawa Univ. |
Hierarchical Lossless Image Coding Using CNN Predictors Optimized by Adaptive Differential Evolution Yuki Kawai, Yuki Nagano, Hideharu Toda, Hisashi Aomori (Chukyo Univ.), Tsuyoshi Otake (Tamagawa Univ.), Ichiro Matsuda, Susumu Itoh (TUS) NLP2018-59 |
We have been proposed on hierarchical lossless image coding using predictors composed of Cellular Neural Network(CNN).Th... [more] |
NLP2018-59 pp.35-38 |
NLP |
2017-07-13 15:45 |
Okinawa |
Miyako Island Marine Terminal |
A Study of Image Inpainting Methods by using SD-CNN Ryohei Mizutani, Hideharu Toda, Hisashi Aomori (Chukyo Univ.), Sathit Prasomphan (King Mongkut Univ. of Tech. North Bangkok), Mamoru Tanaka (Sophia Univ.) NLP2017-37 |
In recent years, the practical use of digital images have been progressed because of the popularization and advance of i... [more] |
NLP2017-37 pp.53-57 |
NLP |
2017-03-14 11:15 |
Aomori |
Nebuta Museum Warasse |
Hierarchical Lossless Image Coding using Inheritance of Predictor-Prototypes and Designing of CNN Predictors based on Estimate of Coding Bits Hideharu Toda (Chukyo Univ.), Tsuyoshi Otake (Tamagawa Univ.), Ichiro Matsuda, Susumu Itoh (TUS), Hisashi Aomori (Chukyo Univ.) NLP2016-109 |
We proposed a hierarchical lossless image coding method using cellular neural network (CNN). It performs adaptive multi ... [more] |
NLP2016-109 pp.19-24 |
NLP |
2016-12-13 10:30 |
Aichi |
Chukyo Univ. |
Particle Swarm Optimization with Refractory Period of Particle Velocity Update Yuki Nagano, Hideharu Toda (Chukyo Univ.), Masatoshi Sato (Tokyo Metropolitan Univ.), Hisashi Aomori (Chukyo Univ.) NLP2016-94 |
Particle Swarm Optimization (PSO) is one of the metaheuristics where each particles in a swarm searches an optimal solut... [more] |
NLP2016-94 pp.55-59 |
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