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 |