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 Conference Papers (Available on Advance Programs)  (Sort by: Date Descending)
 Results 1 - 20 of 97  /  [Next]  
Committee Date Time Place Paper Title / Authors Abstract Paper #
PRMU, IBISML, IPSJ-CVIM 2024-03-03
17:00
Hiroshima Hiroshima Univ. Higashi-Hiroshima campus
(Primary: On-site, Secondary: Online)
Multi-agent reinforcement learning based control method for large-scale crowd movement on Mojiko Fireworks Festival dataset
Kazuya Miyazaki, Masato Kiyama, Motoki Amagasaki, Toshiaki Okamoto (Kumamoto Univ.) IBISML2023-45
The importance of human flow guidance is increasing in response to accidents at events. In recent years, some research h... [more] IBISML2023-45
pp.36-43
NC, MBE, NLP, MICT
(Joint) [detail]
2024-01-24
14:00
Tokushima Naruto University of Education Exploration of Soft Palate Image Based Diagnostic System for High-Risk Individuals of Esophageal Cancer
Keishi Okubo, Masato Kiyama, Motoki Amagasaki, Kotaro Waki, Katsuya Nagaoka, Yasuhito Tanaka (Kumamoto Univ.) NC2023-41
Previous studies have shown that certain findings of the soft palate are associated with the risk of esophageal squamous... [more] NC2023-41
pp.17-22
IBISML 2023-12-21
10:30
Tokyo National Institute of Informatics
(Primary: On-site, Secondary: Online)
Badminton Rally Analysis Using LSTM
Atsushi Yoshinaga, Masato Kiyama, Motoki Amagasaki (Kumamoto Univ.) IBISML2023-35
In this study, we analyze badminton rallies as a tactical support technology for sports using AI. In badminton, it is re... [more] IBISML2023-35
pp.31-36
VLD, DC, RECONF, ICD, IPSJ-SLDM
(Joint) [detail]
2021-12-01
10:35
Online Online Basic evaluation of ReNA, a DNN accelerator using numerical representation posit
Yasuhiro Nakahara, Yuta Masuda, Masato Kiyama, Motoki Amagasaki, Masahiro Iida (Kumamoto Univ.) VLD2021-24 ICD2021-34 DC2021-30 RECONF2021-32
In Convolutional Neural Network (CNN) accelerators for edge, numerical precision of data should be reduced as much as po... [more] VLD2021-24 ICD2021-34 DC2021-30 RECONF2021-32
pp.43-48
RECONF 2021-06-08
16:10
Online Online Automatic generation of executable code for ReNA
Yuta Masuda, Yasuhiro Nakahara, Motoki Amagasaki, Masahiro Iida (Kumamoto Univ.) RECONF2021-6
We have been developing ReNA as a CNN accelerator for the edge, which is controlled by directly specifying control signa... [more] RECONF2021-6
pp.26-31
HWS, VLD [detail] 2021-03-03
11:15
Online Online The Design and Development of of Quantized Neural Networks Library for Exact Hardware Emulation
Masato Kiyama, Yasuhiro Nakahara, Motoki Amagasaki, Masahiro Iida (Kumamoto Univ.) VLD2020-70 HWS2020-45
Quantization is used to speed up execution time and save power when runnning Deep neural networks (DNNs) on edge devices... [more] VLD2020-70 HWS2020-45
pp.18-23
CPSY, RECONF, VLD, IPSJ-ARC, IPSJ-SLDM [detail] 2021-01-26
12:45
Online Online SLM based FPGA-IP soft core
Yuya Nakazato, Hiroaki Koga (Kumamoto Univ.), Zhao Qian (KIT), Motoki Amagasaki, Morihiro Kuga, Masahiro Iida (Kumamoto Univ.) VLD2020-61 CPSY2020-44 RECONF2020-80
In the recent edge computing infrastructure, MEC (Multi-access Edge Computing) devices is considered to reduce the load ... [more] VLD2020-61 CPSY2020-44 RECONF2020-80
pp.125-130
NC, NLP
(Joint)
2021-01-21
12:05
Online Online Examination of precipitation estimation using atmospheric variables
Takanori Ito, Motoki Amagasaki, Kei Ishida, Masato Kiyama, Masahiro Iida (GSST Kumamoto University) NC2020-34
In this paper, we developed a model for SR using ConvLSTM to improve the resolution of precipitation data.
In the relat... [more]
NC2020-34
pp.13-17
MBE, NC
(Joint)
2020-12-18
14:50
Online Online Super resolution for sea surface temperature with CNN and GAN
Tomoki Izumi, Motoki Amagasaki, Kei Ishida, Masato Kiyama (Kumamoto Univ.) NC2020-28
In this paper, we use the deep neural networks (DNN)-based single image super-resolution (SISR) method for the super res... [more] NC2020-28
pp.1-6
VLD, DC, RECONF, ICD, IPSJ-SLDM
(Joint) [detail]
2020-11-17
10:20
Online Online R-GCN Based Function Inference for An Arithmetic Circuit
Yuichiro Fujishiro, Motoki Amagasaki, Masahiro Iida (Kumamoto Univ.), Hiroto Ito, Daisuke Ido (MITSUBISHI ELECTRIC ENGINEERING) VLD2020-21 ICD2020-41 DC2020-41 RECONF2020-40
R-GCN (Relational Graph Convolutional Network) is a convolutional neural network model for graphs consisting of nodes an... [more] VLD2020-21 ICD2020-41 DC2020-41 RECONF2020-40
pp.60-65
VLD, DC, RECONF, ICD, IPSJ-SLDM
(Joint) [detail]
2020-11-17
10:45
Online Online Implementation of YOLO in the AI accelerator ReNA
Toma Uemura, Yasuhiro Nakahara, Motoki Amagasaki, Masato Kiyama, Masahiro Iida (Kumamoto Univ.) VLD2020-22 ICD2020-42 DC2020-42 RECONF2020-41
The object detection,which is a typical AI process,has been attracting attention in various fields because it can identi... [more] VLD2020-22 ICD2020-42 DC2020-42 RECONF2020-41
pp.66-71
VLD, DC, CPSY, RECONF, ICD, IE, IPSJ-SLDM, IPSJ-EMB, IPSJ-ARC
(Joint) [detail]
2019-11-13
10:30
Ehime Ehime Prefecture Gender Equality Center Gate Level Netlist Function Classification Method Based on R-GCN
Yuichiro Fujishiro, Hiroki Oyama, Motoki Amagasaki, Masahiro Iida (Kumamoto Univ.), Hiroaki Yasuda, Hiroto Ito (MITSUBISHI ELECTRIC ENGINEERING) VLD2019-30 DC2019-54
 [more] VLD2019-30 DC2019-54
pp.7-12
VLD, DC, CPSY, RECONF, ICD, IE, IPSJ-SLDM, IPSJ-EMB, IPSJ-ARC
(Joint) [detail]
2019-11-14
10:05
Ehime Ehime Prefecture Gender Equality Center DNN accelerator for AI edge computing
Yasuhiro Nakahara, Juntaro Chikama, Motoki Amagasaki (Kumamoto Univ.), Zhao Qian (Kyutech), Masahiro Iida (Kumamoto Univ.) RECONF2019-38
Convolutional Neural Network (CNN), a kind of artificial intelligence for image recognition, is used in
various fields ... [more]
RECONF2019-38
pp.15-20
RECONF 2019-09-20
14:00
Fukuoka KITAKYUSHU Convention Center Quantized Neural Networks Library for Exact Hardware Emulation
Masato Kiyama, Yasuhiro Nakahara, Motoki Amagasaki, Masahiro Iida (Kumamoto Univ.) RECONF2019-33
Deep neural networks (DNNs) have recently shown outstanding performance in many application domains.
However, it is dif... [more]
RECONF2019-33
pp.69-74
RECONF 2019-05-09
16:35
Tokyo Tokyo Tech Front A case study of an FPGA implementation for streaming data filtering
Hiroki Nakagawa, Yasutaka TsuTsumi, Morihiro Kuga, Motoki Amagasaki, Masahiro Iida, Toshinori Sueyoshi (Kumamoto Univ.) RECONF2019-8
With the spread of IoT (Internet of Things) equipment in recent years, collection of big data becomes easy, and the dema... [more] RECONF2019-8
pp.41-46
RECONF 2019-05-10
13:55
Tokyo Tokyo Tech Front Deep Learning Framework with Numerical Precision
Masato Kiyama, Motoki Amagasaki, Masahiro Iida (Kumamoto Univ.) RECONF2019-15
 [more] RECONF2019-15
pp.79-84
VLD, DC, CPSY, RECONF, CPM, ICD, IE, IPSJ-SLDM, IPSJ-EMB, IPSJ-ARC
(Joint) [detail]
2018-12-05
14:15
Hiroshima Satellite Campus Hiroshima Basic Evaluation of Netlist Function Inference using GCN
Hiroki Oyama, Motoki Amagasaki, Masahiro Iida (kumamoto Univ.), Hiroaki Yasuda, Hiroto Ito (MITSUBISHI ELECTRIC ENGINEERING) VLD2018-44 DC2018-30
In recent years, Recently GCN studies on graphs has been conducted.GCN is a kind of deep learning and classifies network... [more] VLD2018-44 DC2018-30
pp.31-36
VLD, DC, CPSY, RECONF, CPM, ICD, IE, IPSJ-SLDM, IPSJ-EMB, IPSJ-ARC
(Joint) [detail]
2018-12-06
09:00
Hiroshima Satellite Campus Hiroshima Resources Utilization of Fine-grained Overlay Architecture
Theingi Myint (Kumamoto), Qian Zhao (Kyutech), Motoki Amagasaki, Masahiro Iida, Toshinori Sueyoshi (Kumamoto) RECONF2018-37
This paper focuses on utilization of hardware resources for fine-grained overlay architecture. Overlay architectures inc... [more] RECONF2018-37
pp.15-20
RECONF 2018-09-17
14:30
Fukuoka LINE Fukuoka Cafe Space A Case Study on Complex Event Processing over low cost ARM+FPGA Boards.
Hendarmawan (Kumamoto University), Qian Zhao (Kyutech), Motoki Amagasaki, Masahiro Iida, Morihiro Kuga, Toshinori Sueyoshi (Kumamoto University) RECONF2018-21
 [more] RECONF2018-21
pp.13-18
RECONF 2018-09-18
15:15
Fukuoka LINE Fukuoka Cafe Space A case study of database filtering on streaming processing
Hiroki Nakagawa, Morihiro Kuga, Motoki Amagasaki, Masahiro Iida, Toshinori Sueyoshi (Kumamoto Univ.) RECONF2018-33
With the spread of IoT (Internet of Things) equipment in recent years, collection of big data becomes easy, and the dema... [more] RECONF2018-33
pp.79-84
 Results 1 - 20 of 97  /  [Next]  
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