Committee |
Date Time |
Place |
Paper Title / Authors |
Abstract |
Paper # |
NC, NLP (Joint) |
2025-01-29 14:30 |
Osaka |
(Osaka) |
Effects of Introducing Gap Junctions into Spiking Neural Networks on Handwritten Digit Classification Shinnosuke Touda, Akito Morita, Hirotsugu Okuno (OIT) NC2024-56 |
We investigated the effect of introducing gap junctions on the classification of handwritten digits in a winner-take-all... [more] |
NC2024-56 pp.79-83 |
VLD, DC, RECONF, ICD, IPSJ-SLDM [detail] |
2024-11-12 14:30 |
Oita |
COMPAL HALL (Oita, Online) (Primary: On-site, Secondary: Online) |
Efficient inference method using adaptive variable time steps in SNN Naoya Watanabe, Yoshinori Takeuchi (Kindai) VLD2024-29 ICD2024-47 DC2024-51 RECONF2024-59 |
Artificial intelligence is now widely used in private life and business, and its application requires learning that invo... [more] |
VLD2024-29 ICD2024-47 DC2024-51 RECONF2024-59 pp.14-19 |
MRIS, CPM, ITE-MMS [detail] |
2024-11-01 12:10 |
Nagano |
Nagano Camp. Shinshu Univ. + Online (Nagano, Online) (Primary: On-site, Secondary: Online) |
[Invited Talk]
Development of oxide-based leaky-integrating transistor for spiking neural networks Hisashi Inoue (AIST), Hiroto Tamura (Univ. Tokyo), Ai Kitoh (AIST), Xiangyu Chen, Zolboo Byambadorj (Univ. Tokyo), Takeaki Yajima (Kyushu Univ.), Yasushi Hotta (Univ. Hyogo), Tetsuya Iizuka (Univ. Tokyo), Gouhei Tanaka (Univ. Tokyo/Nagoya Inst. Tech.), Isao Inoue (AIST) MRIS2024-26 CPM2024-55 |
Biomimetic computing aims to realize energy-efficient information processing by mimicking the behavior of biological neu... [more] |
MRIS2024-26 CPM2024-55 pp.77-80 |
NC, MBE (Joint) |
2024-09-27 15:40 |
Miyagi |
Tohoku Univ. (Miyagi, Online) (Primary: On-site, Secondary: Online) |
Analog CMOS circuit implementation of STDP and its application to classification tasks Yosuke Iida, Satoshi Moriya, Hideaki Yamamoto, Shigeo Sato (Tohoku Univ) NC2024-37 |
STDP, a learning rule suitable for spiking neural networks, learns from local spike timing differences between neurons. ... [more] |
NC2024-37 pp.29-32 |
NC, MBE, NLP, MICT (Joint) [detail] |
2024-01-25 11:50 |
Tokushima |
Naruto University of Education (Tokushima) |
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 |
NLP |
2023-05-13 10:00 |
Fukushima |
Kenshin Koriyama Cultural Center (Koriyama, Fukushima) (Fukushima) |
A Study of Ergodic Sequential Circuit Neuronal Networks for Use in Neuroprosthetic Devices Yuta Shiomi, Hiroyuki Torikai (Hosei Univ.) NLP2023-1 |
In this study, we propose a network based on an ergodic ordered circuit neuron model.
We show that the proposed model c... [more] |
NLP2023-1 pp.1-4 |
NLP, MSS |
2023-03-15 15:15 |
Nagasaki |
(Nagasaki, Online) (Primary: On-site, Secondary: Online) |
Hippocampal CA3 spiking neural network model for constructing never-experienced novel path sequences on a maze task Kensuke Takada, Katsumi Tateno (Kyushu Inst. Tech.) MSS2022-74 NLP2022-119 |
Hippocampal neurons that represent the animal's self-location are called "place cells." In the maze task in rodents, hip... [more] |
MSS2022-74 NLP2022-119 p.64 |
NC, NLP |
2023-01-29 10:15 |
Hokkaido |
Future University Hakodate (Hokkaido, Online) (Primary: On-site, Secondary: Online) |
Low complexity of neural activity caused by weak inhibition in spiking neural networks Jihoon Park (NICT/Osaka Univ.), Yuji Kawai (Osaka Univ.), Minoru Asada (IPUT Univ./Osaka Univ./Chubu Univ./NICT) NLP2022-96 NC2022-80 |
The balance between excitatory and inhibitory neuronal activities (E/I) is an essential factor to perform normal functio... [more] |
NLP2022-96 NC2022-80 pp.81-86 |
NC, MBE (Joint) |
2022-09-29 10:25 |
Miyagi |
Tohoku Univ. (Miyagi, Online) (Primary: On-site, Secondary: Online) |
Analog circuit implementation of spiking neural networks and its application to time-series information processing Satoshi Moriya, Hideaki Yamamoto (Tohoku Univ), Yasushi Yuminaka (Gunma Univ.), Shigeo Sato, Yoshihiko Horio (Tohoku Univ) NC2022-33 |
Edge computing in which low-dimensional signals such as sensor output are processed nearby sensors have become increasin... [more] |
NC2022-33 p.5 |
MSS, NLP |
2022-03-29 09:40 |
Online |
Online (Online) |
Effects of sparse connections in spiking neural networks for unsupervised pattern recognition Hiroki Shinagawa, Kantaro Fujiwara, Gouhei Tanaka (Univ. of Tokyo) MSS2021-69 NLP2021-140 |
Recently, the spiking neural network (SNN) models, which compute using spatio-temporal information representation by neu... [more] |
MSS2021-69 NLP2021-140 pp.71-76 |
VLD, HWS [detail] |
2022-03-07 15:05 |
Online |
Online (Online) |
Low-Energy and Fast Inference Method for Spiking Neural Networks Using Dynamic Threshold Adjustment Takehiro Habara, Hiromitsu Awano (Kyoto Univ.) VLD2021-87 HWS2021-64 |
Conventional SNNs have fixed thresholds that determine the possibility of neuron firing, resulting in degradation of inf... [more] |
VLD2021-87 HWS2021-64 pp.57-62 |
MBE, NC (Joint) |
2022-03-03 11:10 |
Online |
Online (Online) |
Basic characteristics of SAM spiking neuron model with rate coding Minoru Motoki (Kumamoto KOSEN) NC2021-63 |
he SAM neuron model is one of spiking neural networks that have high computational efficiency and familiarity for digita... [more] |
NC2021-63 pp.88-93 |
RECONF, VLD, CPSY, IPSJ-ARC, IPSJ-SLDM [detail] |
2022-01-24 17:10 |
Online |
Online (Online) |
Ternarizing Deep Spiking Neural Network Man Wu, Yirong Kan, Van_Tinh Nguyen, Renyuan Zhang, Yasuhiko Nakashima (NAIST) VLD2021-61 CPSY2021-30 RECONF2021-69 |
The feasibility of ternarizing spiking neural networks (SNNs) is studied in this work toward trading a slight accuracy f... [more] |
VLD2021-61 CPSY2021-30 RECONF2021-69 pp.67-72 |
MBE, NC (Joint) |
2021-10-28 15:05 |
Online |
Online (Online) |
Enhancement of spatio-temporal coding performance in spiking neural network and its application to hazard detection for landing of spacecrafts Hideaki Kinoshita, Shinichi Kimura (TUS), Seisuke Fukuda (JAXA) NC2021-21 |
Spiking neural networks (SNNs) are a neuromimetic computational architecture that has attracted much attention in recent... [more] |
NC2021-21 pp.16-21 |
CCS |
2020-11-26 15:25 |
Online |
Online (Online) |
Synthesis and implementation of digital spiking neurons Tomoki Harada, Toshimichi Saito (HU) CCS2020-18 |
This paper studies implementation of desired digital spike-trains based on simple evolutionary algorithm.
First, the dy... [more] |
CCS2020-18 pp.6-10 |
MBE, NC, NLP, CAS (Joint) [detail] |
2020-10-29 15:20 |
Online |
Online (Online) |
Unsupervised learning based on local interactions between reservoir and readout neurons Tstuki Kato, Satoshi Moriya, Hideaki Yamamoto, Masao Sakuraba, Shigeo Sato (Tohoku Univ.) NC2020-12 |
Reservoir computing is suitable for implementations in edge computing devices thanks to its low computational cost and e... [more] |
NC2020-12 pp.21-23 |
IPSJ-SLDM, RECONF, VLD, CPSY, IPSJ-ARC [detail] |
2020-01-23 14:45 |
Kanagawa |
Raiosha, Hiyoshi Campus, Keio University (Kanagawa) |
Study of a Simplified Digital Spiking Neuron and Its FPGA Implementation Tomohiro Yoneda (NII) VLD2019-75 CPSY2019-73 RECONF2019-65 |
A simplified digital spiking neural network implementable on FPGAs is proposed in order to reduce necessary resources an... [more] |
VLD2019-75 CPSY2019-73 RECONF2019-65 pp.135-140 |
NC, MBE |
2019-12-06 10:10 |
Aichi |
Toyohashi Tech (Aichi) |
Implementation of Cerebellar Spiking Neural Network Model on a FPGA Yusuke Shinji (Chubu Univ.), Hirotsugu Okuno (OIT), Yutaka Hirata (Chubu Univ.) MBE2019-46 NC2019-37 |
The cerebellum is crucially involved in motor control and learning. Its neuronal network architecture and firing propert... [more] |
MBE2019-46 NC2019-37 pp.7-12 |
NC, IBISML, IPSJ-MPS, IPSJ-BIO [detail] |
2019-06-17 14:15 |
Okinawa |
Okinawa Institute of Science and Technology (Okinawa) |
Effects of excitatory/inhibitory balance of a spiking neuron model on the organization of neural network Jihoon Park, Motohiro Ogura, Yuji Kawai, Minoru Asada (Osaka Univ.) NC2019-4 |
In this study, a spiking neural network model is examined to study how the balance between excitatory and inhibitory neu... [more] |
NC2019-4 pp.15-20 |
OME, SDM |
2019-04-26 13:10 |
Kagoshima |
Yakushima Environmental and Culture Village Center (Kagoshima) |
Information processing using molecular network system Takuya Matsumoto (Osaka Univ.) SDM2019-4 OME2019-4 |
In recent decades, studies on the electronic properties and functions of single molecules have made significant advances... [more] |
SDM2019-4 OME2019-4 pp.13-17 |