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 Conference Papers (Available on Advance Programs)  (Sort by: Date Descending)
 Results 1 - 20 of 209  /  [Next]  
Committee Date Time Place Paper Title / Authors Abstract Paper #
IT, EMM 2024-05-30
15:35
Chiba Chiba University (Nishi-Chiba Campus) On the Complexity of Codewords on Fixed-to-Fixed Length Source Coding
Mitsuharu Arimura, Mitsugu Iwamoto (UEC)
(To be available after the conference date) [more]
RCC, ISEC, IT, WBS 2024-03-14
10:20
Osaka Osaka Univ. (Suita Campus) IT2023-111 ISEC2023-110 WBS2023-99 RCC2023-93 This paper deals with variable-length lossy source coding in which the criteria are a cumulant generating function of co... [more] IT2023-111 ISEC2023-110 WBS2023-99 RCC2023-93
pp.238-240
SS 2024-03-09
10:35
Okinawa
(Primary: On-site, Secondary: Online)
Considerations of an Automatic Feedback Method for a Learner's Editing Source Codes in Programming Exercises -- Guided Feedback Using Edit Transition Graphs of a Model Answer Program --
Yuki Sawada, Yoshinari Hachisu, Atsushi Yoshida, Hiroaki Kuwabara (Nanzan Univ.) SS2023-78
In programming exercises, it is difficult for some learners to complete source codes by themselves. Many researches on a... [more] SS2023-78
pp.174-179
SIP, SP, EA, IPSJ-SLP [detail] 2024-02-29
16:20
Okinawa
(Primary: On-site, Secondary: Online)
Comparison of DNN architectures for determined BSS by proximal average of IVA and DNN
Kazuki Matsumoto (Waseda Univ.), Koki Yamada, Kohei Yatabe (TUAT) EA2023-88 SIP2023-135 SP2023-70
We have proposed a framework called PA-BSS for high-performance separation matrix estimation using deep denoisers based ... [more] EA2023-88 SIP2023-135 SP2023-70
pp.162-167
CS 2023-11-09
10:55
Shizuoka Plaza Verde Deep Joint Source-Channel Coding using Overlap Image Division for Block Noise Reduction
Ryunosuke Yamamoto, Yoshiaki Inoue, Daisuke Hisano (Osaka Univ.) CS2023-65
Deep Joint Source-Channel Coding (Deep JSCC), which uses deep learning to perform source and channel coding simultaneous... [more] CS2023-65
pp.16-18
SR 2023-11-10
11:10
Miyagi
(Primary: On-site, Secondary: Online)
[Short Paper] Model Sharing and Learning for Visually Secure Deep Joint Source Channel Coding
Yuyang Fu, Katsuya Suto (UEC) SR2023-59
Research and development of Deep Joint Source Channel Coding (DeepJSCC) technology, which is a data-driven design of inf... [more] SR2023-59
pp.64-66
MIKA
(3rd)
2023-10-11
14:30
Okinawa Okinawa Jichikaikan
(Primary: On-site, Secondary: Online)
[Poster Presentation] Performance Evaluation of MIMO Transmission in Information Source Communication Channel Batch Coded Modulation Based on Deep Learning
Shion Inokuma, Yuki Sasaki (Tokyo Univ. of Science), Daisuke Hisano (Osaka Univ.), Yu Nakayama (TUAT), Kazuki Maruta (Tokyo Univ. of Science)
We present the results of a fundamental investigation of deep learning-based Joint Source-Channel Coding and Modulation ... [more]
IT 2023-08-03
13:25
Kanagawa Shonan Institute of Technology
(Primary: On-site, Secondary: Online)
Polarization Analysis for Joint Source-Channel Coding with Side Information
Yuki Nagai, Hideki Yagi (UEC) IT2023-15
The polar codes, introduced by Arıkan, use a technique called channel polarization and can achieve the capacity of a giv... [more] IT2023-15
pp.7-12
IT 2023-08-03
14:30
Kanagawa Shonan Institute of Technology
(Primary: On-site, Secondary: Online)
An Asymmetric Encoding-Decoding Scheme for Lossless Data Compression
Hirosuke Yamamoto (Univ. of Tokyo), Ken-ichi Iwata (Univ. of Fukui) IT2023-17
ANS (Asymmetric Numeral Systems) are new lossless data-compression-coding systems that can achieve almost the same compr... [more] IT2023-17
pp.17-22
MSS, CAS, SIP, VLD 2023-07-06
17:00
Hokkaido
(Primary: On-site, Secondary: Online)
[Invited Talk] Introduction of NanoVNA -- Open Source Handheld Verctor Network Analyzer --
Tomohiro Takahashi (CM) CAS2023-14 VLD2023-14 SIP2023-30 MSS2023-14
This talk shows an overview of NanoVNA, an ultra-compact vector network analyzer. I developed NanoVNA and pushed the res... [more] CAS2023-14 VLD2023-14 SIP2023-30 MSS2023-14
p.71
SANE 2023-05-23
15:40
Kanagawa Information Technology R & D Center, MITSUBISHI Electric Corp.
(Primary: On-site, Secondary: Online)
Radar Cross-Section of Point Source Groups Envisaging Chaff Clouds Using Near-Field to Far-Field Transformation
Hirokazu Kobayashi (Electromagnetic Wave System Lab.), Yousuke Aoi, Hirohisa Oda (SOGO) SANE2023-13
A theoretical study for the radar cross sections (RCS) of chaff clouds is discussed using a software code that incorpora... [more] SANE2023-13
pp.72-77
SR 2023-05-11
15:10
Hokkaido Center of lifelong learning Kiran (Higashi Muroran)
(Primary: On-site, Secondary: Online)
[Short Paper] Continuous Compressible Deep Joint Source Channel Coding
Junichiro Yamada, Katsuya Suto (UEC) SR2023-11
Deep Joint Source Channel Coding (DeepJSCC), which designs a source and channel coding model with deep neural networks a... [more] SR2023-11
pp.58-60
SS 2023-03-14
18:25
Okinawa
(Primary: On-site, Secondary: Online)
A feature analysis of merged change requests on a version
Mizuki Uenaka, Akinori Ihara (Wakayama Univ.), Yutaro Kashiwa (NAIST) SS2022-60
Large software development projects have a large number of the source code change requests on a daily basis. Developers ... [more] SS2022-60
pp.79-84
SS 2023-03-15
15:15
Okinawa
(Primary: On-site, Secondary: Online)
Attempt to generate source code using previous token type information
Shun Tanaka, Yamamoto Tetsuo (Ryukoku Univ.) SS2022-70
In this study, we improve the BeamSearch algorithm used in the machine Learning model. We add an process to the token se... [more] SS2022-70
pp.139-144
RCC, ISEC, IT, WBS 2023-03-14
13:00
Yamaguchi
(Primary: On-site, Secondary: Online)
Exponential Strong Converse for Source Coding with Encoded Side Information -- Comparison with Source Coding with Non-encoded Side Information --
Daisuke Takeuchi, Shun Watanabe (TUAT) IT2022-100 ISEC2022-79 WBS2022-97 RCC2022-97
The source coding problem with encoded side information is considered. A lower bound on the strong converse exponent has... [more] IT2022-100 ISEC2022-79 WBS2022-97 RCC2022-97
pp.209-211
RCC, ISEC, IT, WBS 2023-03-14
13:50
Yamaguchi
(Primary: On-site, Secondary: Online)
A Construction Method of Alphabetic Codes Allowing N-bit Decoding Delays
Daichi Ueda, Ken-ichi Iwata (Univ. of Fukui), Hirosuke Yamamoto (The Univ. of Tokyo) IT2022-102 ISEC2022-81 WBS2022-99 RCC2022-99
As an extension of the AIFV and AIFV-m codes that allow decoding delay, Sugiura, Kamamoto, and Moriya proposed the N-bit... [more] IT2022-102 ISEC2022-81 WBS2022-99 RCC2022-99
pp.218-223
RCC, ISEC, IT, WBS 2023-03-14
14:15
Yamaguchi
(Primary: On-site, Secondary: Online)
Construction of Grammar-Based Codes Using the LZ78 Code and Its Variants
Mitsuharu Arimura (Shonan Inst. Tech.) IT2022-103 ISEC2022-82 WBS2022-100 RCC2022-100
It is shown by Kieffer and Yang that Lempel-Ziv78 (LZ78) method can be implemented as a variation of grammar-based code.... [more] IT2022-103 ISEC2022-82 WBS2022-100 RCC2022-100
pp.224-229
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
IT, RCS, SIP 2023-01-24
10:25
Gunma Maebashi Terrsa
(Primary: On-site, Secondary: Online)
An improved context tree switching method by dynamic expansion and pruning of context tree
Masaya Ootsu, Hideki Yagi (UEC) IT2022-36 SIP2022-87 RCS2022-215
The Context Tree Weighting (CTW) method is a sequential lossless universal coding algorithm for tree sources with good p... [more] IT2022-36 SIP2022-87 RCS2022-215
pp.42-47
IT, RCS, SIP 2023-01-24
10:50
Gunma Maebashi Terrsa
(Primary: On-site, Secondary: Online)
Lower Bound on Maximum Redundancy of Predictive Source Coding for Context Tree Source
Shota Saito (Gunma Univ.) IT2022-37 SIP2022-88 RCS2022-216
In [Krichevskiy, IEEE Trans. Inf. Theory, vol.44, no.1, pp.296--303, 1998], a lower bound of the maximum redundancy of a... [more] IT2022-37 SIP2022-88 RCS2022-216
pp.48-50
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