Hiroshi Saito

University of Aizu

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Design of Asynchronous CNN Circuits on Commercial FPGA from Synchronous CNN Circuits

Hayato Kato Hiroshi Saito

To accelerate performance, Convolutional Neural Networks (CNNs) are frequently used in Field Programmable Gate Arrays (FPGAs). In this paper, to reduce the power consumption of CNN circuits, we propose a design method to design asynchronous CNN circuits on commercial FPGAs. First, the proposed method converts Register Transfer Level (RTL) models of synchronous CNN circuits to RTL models of asynchronous CNN circuits. Then, the proposed method designs asynchronous CNN circuits using a commercial FPGA design environment. In the experiment, we designed an asynchronous CNN circuit and evaluated the performance. Compared to the synchronous counterpart, the asynchronous CNN circuit consumed about 2.3% less energy.

Asynchronous circuit

Asynchronous system

10.1109/mcsoc.2019.00016

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Citations (4)

A Study of Dynamic Power Optimization by Latch Insertion for Asynchronous RTL Models

IEICE Technical Report; IEICE Tech. Rep. (2020)

Shogo Semba Hiroshi Saito

Dynamic demand

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Citations (0)

Environmental remediation for the upstream of Yotsugi Mill Tailings Pond, Ningyo-toge Uranium Mine

Hiroshi Saito Kazuyoshi Torikai Shigeru Fukushima Ryota Sakao Tomihiro Taki

Uranium mine

Uranium ore

10.11484/jaea-technology-2015-063

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Cell-level Simulation with ATM Traffic Monitoring Tool

日本オペレーションズ・リサーチ学会秋季研究発表会アブストラクト集 (1999)

Hiroshi Saito Toshiaki Tsuchiya Shoichiro Asano

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A Behavioral Synthesis System for Asynchronous Circuits with Bundled-data Implementation

IPSJ Transactions on System and LSI Design Methodology (2009)

Naohiro Hamada Yuki Shiga Takao Konishi Hiroshi Saito Tomohiro Yoneda

This paper proposes a behavioral synthesis system for asynchronous circuits with bundled-data implementation. The proposed system is based on a behavioral synthesis method for synchronous circuits and extended on operation scheduling and control synthesis for bundled-data implementation. The proposed system synthesizes an RTL model and a simulation model from a behavioral description specified by a restricted C language, a resource library, and a set of design constraints. This paper shows the effectiveness of the proposed system in terms of area and latency through comparisons among bundled-data implementations synthesized by the proposed system, synchronous counterparts, and bundled-data implementations synthesized by using a behavioral synthesis method for synchronous circuits directly.

Implementation

Behavioral Modeling

High-Level Synthesis

10.2197/ipsjtsldm.2.64

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Citations (3)

Logic Optimization for Asynchronous SI Controllers using Transduction Method.

Hiroshi Saito Hiroshi Nakamura Masahiro Fujita Takashi Nanya

Transduction (biophysics)

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Contactless monitoring of human behaviors in bed using RSSI signals

Medical & Biological Engineering & Computing (2023)

Peeradon Thammachote Chawakorn Intongkum Kiattisak Sengchuai Nattha Jindapetch Pornchai Phukpattaranont

Sitting

Sleep

SIGNAL (programming language)

Human physiology

Signal strength

10.1007/s11517-023-02847-6

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Citations (6)

Reliable and Efficient Bear-presence Detection based on Region Proposal of Low-resolution

2022 IEEE International Conference on Systems, Man, and Cybernetics (SMC) (2020)

Masayuki Tokutake Kaisei Shimura Yoichi Tomioka Hiroshi Saito Yukihide Kohira

The bear attack to human beings is one of the fatal accidents, and it is becoming more critical to avoid such accidents because human 's encountering a bear happens every year, even in a city area. It is required to discover bears quickly and warn people to avoid bear accidents. To realize sensor nodes that detect bears automatically using image recognition technology, we aim to realize an accurate and computationally-efficient bear-presence detection. In this paper, we propose a bear-presence detection method combining region proposal of a low-resolution and image classification. In the experiments, we show that the proposed method achieves 4.9% higher recall and 2.3% higher F-score than image classification with-out region-proposal. Moreover, the proposed method achieved 0.6% higher recall and 18.5% higher F-score than YOLOv3, which is one of state-of-the-art object detection methods while the execution time was reduced to 72.4% for bear images and 55.5% for non-bear images.

Low resolution

10.1109/smc42975.2020.9283097

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Citations (1)

Mitigation of methane emissions from paddy fields by prolonging midseason drainage

Agriculture Ecosystems & Environment (2011)

Masayuki Itoh Shigeto Sudo Shizuka Mori Hiroshi Saito Takahiro Yoshida

Nitrous oxide

Paddy field

Global-warming potential

Tonne

10.1016/j.agee.2011.03.019