8 citations · 12 across the 6 of their papers we have counts for
8 papers
Hibikino-Musashi@Home 2022 Team Description Paper
Tomoya Shiba, Tomohiro Ono, Shoshi Tokuno +27
Our team, Hibikino-Musashi@Home (HMA), was founded in 2010. It is based in Japan in the Kitakyushu Science and Research Park. Since 2010, we have annually participated in the RoboC…
Hibikino-Musashi@Home 2018 Team Description Paper
Yutaro Ishida, Sansei Hori, Yuichiro Tanaka +14
Our team, Hibikino-Musashi@Home (the shortened name is HMA), was founded in 2010. It is based in the Kitakyushu Science and Research Park, Japan. We have participated in the RoboCu…
Effects of VLSI Circuit Constraints on Temporal-Coding Multilayer Spiking Neural Networks
Yusuke Sakemi, Takashi Morie, Takeo Hosomi +1
The spiking neural network (SNN) has been attracting considerable attention not only as a mathematical model for the brain, but also as an energy-efficient information processing m…
Hibikino-Musashi@Home 2019 Team Description Paper
Yuichiro Tanaka, Yutaro Ishida, Yushi Abe +12
Our team, Hibikino-Musashi@Home (HMA), was founded in 2010. It is based in the Kitakyushu Science and Research Park, Japan. Since 2010, we have participated in the RoboCup@Home Jap…
A Supervised Learning Algorithm for Multilayer Spiking Neural Networks Based on Temporal Coding Toward Energy-Efficient VLSI Processor Design
Yusuke Sakemi, Kai Morino, Takashi Morie +1
Spiking neural networks (SNNs) are brain-inspired mathematical models with the ability to process information in the form of spikes. SNNs are expected to provide not only new machi…
An Efficient Hardware-Oriented Dropout Algorithm
Yoeng Jye Yeoh, Takashi Morie, Hakaru Tamukoh
This paper proposes a hardware-oriented dropout algorithm, which is efficient for field programmable gate array (FPGA) implementation. In deep neural networks (DNNs), overfitting o…