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 Conference Papers (Available on Advance Programs)  (Sort by: Date Descending)
 Results 21 - 40 of 1602 [Previous]  /  [Next]  
Committee Date Time Place Paper Title / Authors Abstract Paper #
MI 2024-03-03
14:30
Okinawa OKINAWAKEN SEINENKAIKAN
(Primary: On-site, Secondary: Online)
[Invited Lecture] Latest Research Trends 2023: Machine Learning for Medical Image Processing
Fukashi Yamazaki (Canon) MI2023-48
In this paper, we overview the outlines of MICCAI 2023’s main conference sessions and satellite workshops. Several inter... [more] MI2023-48
pp.53-55
PRMU, IBISML, IPSJ-CVIM 2024-03-04
09:00
Hiroshima Hiroshima Univ. Higashi-Hiroshima campus
(Primary: On-site, Secondary: Online)
PRMU2023-64 (To be available after the conference date) [more] PRMU2023-64
pp.76-81
PRMU, IBISML, IPSJ-CVIM 2024-03-04
09:24
Hiroshima Hiroshima Univ. Higashi-Hiroshima campus
(Primary: On-site, Secondary: Online)
PRMU2023-66 (To be available after the conference date) [more] PRMU2023-66
pp.88-93
PRMU, IBISML, IPSJ-CVIM 2024-03-04
11:16
Hiroshima Hiroshima Univ. Higashi-Hiroshima campus
(Primary: On-site, Secondary: Online)
PRMU2023-73 (To be available after the conference date) [more] PRMU2023-73
pp.128-133
EMM 2024-03-02
16:20
Overseas Day1:JEJU TECHNOPARK, Day2:JEJU Business Agency [Fellow Memorial Lecture] Application of associative memory models to watermarking models
Masaki Kawamura (Yamaguchi Univ.) EMM2023-93
We proposed a new method called the associative watermarking method, which is an extension of the zero-watermarking meth... [more] EMM2023-93
pp.23-27
HCS 2024-03-02
12:05
Shizuoka Tokoha University(Shizuoka-Kusanagi Campus) Estimation of willingness to participate in other's conversation by using deep learning of facial expression measurements
Kohei Yamamoto, Jiro Okuda (Kyoto Sangyo Univ.) HCS2023-92
In recent years, there has been much interest in developing agents that can join conversations among multiple people and... [more] HCS2023-92
pp.25-30
AI 2024-03-01
13:40
Aichi Room0221, Bldg.2-C, Nagoya Institute of Technology Applying Graph Neural Networks and Reinforcement Learning to the Multiple Depot-Multiple Traveling Salesman Problem
Dongyeop Kim, Toshihiro Matsui (NITech) AI2023-39
In this study, we introduce a method combining Graph Neural Networks (GNN) and reinforcement learning for the Multiple D... [more] AI2023-39
pp.13-18
AI 2024-03-01
14:40
Aichi Room0221, Bldg.2-C, Nagoya Institute of Technology Request span extraction from dialog with Heterogeneous Graph Attention Networks
Naoki Mizumoto, Katsuhide Fujita (TUAT) AI2023-41
In this study, we formulate the problem of extracting user requests from the dialogue history as a ``span extraction pro... [more] AI2023-41
pp.25-30
DC 2024-02-28
13:40
Tokyo Kikai-Shinko-Kaikan Bldg. Test Point Selection Method for Multi-Cycle BIST Using Deep Reinforcement Learning
Kohei Shiotani, Tatsuya Nishikawa, Shaoqi Wei, Senling Wang, Hiroshi Kai, Yoshinobu Higami, Hiroshi Takahashi (Ehime Univ.) DC2023-98
Multi-cycle BIST is a test method that performs multiple captures for each scan pattern, proving effective in reducing t... [more] DC2023-98
pp.23-28
VLD, HWS, ICD 2024-03-01
10:10
Okinawa
(Primary: On-site, Secondary: Online)
Fault Detectable Convolutional Neural Network Circuits With Dual Modular Redundancy Based on Mixed-precision Quantization
Yamato Saikawa, Yuta Owada, Yoichi Tomioka, Hiroshi Saito, Yukihide Kohira (UoA) VLD2023-122 HWS2023-82 ICD2023-111
In safety-critical edge AI systems, circuit failures caused by aging or cosmic ray can lead to serious accidents. Dual M... [more] VLD2023-122 HWS2023-82 ICD2023-111
pp.119-124
VLD, HWS, ICD 2024-03-02
09:20
Okinawa
(Primary: On-site, Secondary: Online)
Countermeasure on AI Hardware against Adversarial Examples
Kosuke Hamaguchi, Shu Takemoto, Yusuke Nozaki, Masaya Yoshikawa (Meijo Univ.) VLD2023-134 HWS2023-94 ICD2023-123
The demand for edge AI, in which artificial intelligence (AI) is directly embedded in devices, is increasing, and the se... [more] VLD2023-134 HWS2023-94 ICD2023-123
pp.184-189
EID, ITE-IDY, IEE-EDD, SID-JC, IEIJ-SSL [detail] 2024-01-25
13:15
Kyoto
(Primary: On-site, Secondary: Online)
[Poster Presentation] Reproduction of changes in membrane potential of neurons by synaptic devices using memristors
Kenta Yachida, Yoshiya Abe, Kazuki Sawai (Ryukoku Univ.), Tokiyoshi Matsuda (Kindai Univ./Ryukoku Univ.), Hidenori Kawanishi (Ryukoku Univ.), Mutsumi Kimura (Ryukoku Univ./NAIST) EID2023-4
We attempted to replicate the changes in the membrane potential of neurons using thin-film neuromorphic devices that int... [more] EID2023-4
pp.9-12
PRMU, MVE, VRSJ-SIG-MR, IPSJ-CVIM 2024-01-26
15:46
Kanagawa Keio Univ. (Hiyoshi Campus) PRMU2023-48 In the realm of autonomous driving, end-to-end models (E2EDMs) have gained prominence due to their high predictive accur... [more] PRMU2023-48
pp.46-49
ICTSSL, CAS 2024-01-25
11:45
Kanagawa
(Primary: On-site, Secondary: Online)
Comparison of transfer learning and fine tuning
Ohata Shunsuke, Okazaki Hideaki (SIT) CAS2023-88 ICTSSL2023-41
This report examines the principal image recognition methods. First, we show the experimental results of image recogniti... [more] CAS2023-88 ICTSSL2023-41
pp.31-33
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
NC, MBE, NLP, MICT
(Joint) [detail]
2024-01-25
09:00
Tokushima Naruto University of Education The Relationship Between Metrics in the Latent Variable Space and Image Classification Performance
Haruki Wakasa, Kenya Jin'no (Tokyo City Univ.) NLP2023-99 MICT2023-54 MBE2023-45
In recent years, models based on convolutional neural networks (CNNs) have exhibited high performance in image classific... [more] NLP2023-99 MICT2023-54 MBE2023-45
pp.78-81
NC, MBE, NLP, MICT
(Joint) [detail]
2024-01-25
11:50
Tokushima Naruto University of Education Optimization of synaptic scaling rule, its implementation on modular spiking neural networks and analysis of its affects
Takumi Shinkawa, Hideyuki Kato (Oita Univ.), Yoshitaka Ishikawa (FUN), Takuma Sumi, Hideaki Yamamoto (Tohoku Univ.), Yuichi Katori (FUN) NLP2023-107 MICT2023-62 MBE2023-53
In this study, to theoretically investigate the information processing mechanisms in the brain, we optimized synaptic sc... [more] NLP2023-107 MICT2023-62 MBE2023-53
pp.110-113
SCE 2024-01-23
13:35
Tokyo Kikai-Shinko-Kaikan Bldg.
(Primary: On-site, Secondary: Online)
[Invited Talk] Research on Novel Binary Neural Processing Elements Using Single Flux Quantum Circuits
Zeyu Han, Zongyuan Li, Yamanashi Yuki, Yoshikawa Nobuyuki (Yokohama National Univ.) SCE2023-23
Superconducting convolutional neural networks, based on single flux quantum (SFQ) circuits, hold significant potential d... [more] SCE2023-23
pp.1-6
EMT, PN, MWPTHz, IEE-EMT [detail] 2024-01-22
10:55
Kyoto Kyoto Univ. Yoshida Campus Transmission Characteristics Adaptation of a Microstrip Line Filters Using the Transformer
Keiichiro Yamada, Takashi Kuroki, Naoki Miyata (TMCIT) PN2023-49 EMT2023-89 MWPTHz2023-77
This paper presents new technique for inverse model that can be proposed geometrical parameters of microwave circuit fro... [more] PN2023-49 EMT2023-89 MWPTHz2023-77
pp.11-16
SeMI 2024-01-18
13:30
Yamanashi Raki House Kaiji Enhancing Human Skeleton Estimation with Multi-Frame mmWave Radar Point Cloud-based Method
Xintong Shi, Tomoaki Ohtsuki (Keio Univ.) SeMI2023-52
Millimeter-Wave (mmWave) radar-based skeleton estimation has emerged as a focal point in the realm of human motion analy... [more] SeMI2023-52
pp.18-21
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