Masato Kiyama

According to our database, Masato Kiyama authored at least 16 papers between 2005 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of three.

2024

Multi-Camera People Tracking With Spatio-Temporal and Group Considerations.

Shoki Sakaguchi, Motoki Amagasaki, Masato Kiyama, Toshiaki Okamoto

IEEE Access, 2024

2023

A Lightweight Deep Neural Network Using a Mixer-Type Nonlinear Vector Autoregression.

Mery Diana, Ridhwan Amin, Motoki Amagasaki, Masato Kiyama

IEEE Access, 2023

A Deep Neural Network Translator for Edge Site Implementation.

Mery Diana, Masato Kiyama, Motoki Amagasaki, Masayoshi Ito, Yuki Morishita

Proceedings of the Eleventh International Symposium on Computing and Networking, CANDAR 2023, 2023

2022

A Posit Based Multiply-accumulate Unit with Small Quire Size for Deep Neural Networks.

Yasuhiro Nakahara, Yuta Masuda, Masato Kiyama, Motoki Amagasaki, Masahiro Iida

IPSJ Trans. Syst. LSI Des. Methodol., 2022

Reconfigurable Neural Network Accelerator and Simulator for Model Implementation.

Yasuhiro Nakahara, Masato Kiyama, Motoki Amagasaki, Qian Zhao, Masahiro Iida

IEICE Trans. Fundam. Electron. Commun. Comput. Sci., 2022

2021

Extension of Convolutional Neural Network along Temporal and Vertical Directions for Precipitation Downscaling.

Takeyoshi Nagasato, Kei Ishida, Ali Ercan, Tongbi Tu, Masato Kiyama, Motoki Amagasaki, Kazuki Yokoo

CoRR, 2021

Use of 1D-CNN for input data size reduction of LSTM in Hourly Rainfall-Runoff modeling.

Kei Ishida, Ali Ercan, Takeyoshi Nagasato, Masato Kiyama, Motoki Amagasaki

CoRR, 2021

Development of Quantized DNN Library for Exact Hardware Emulation.

Masato Kiyama, Motoki Amagasaki, Masahiro Iida

CoRR, 2021

Capabilities of Deep Learning Models on Learning Physical Relationships: Case of Rainfall-Runoff Modeling with LSTM.

Kazuki Yokoo, Kei Ishida, Ali Ercan, Tongbi Tu, Takeyoshi Nagasato, Masato Kiyama, Motoki Amagasaki

CoRR, 2021

Multi-Time-Scale Input Approaches for Hourly-Scale Rainfall-Runoff Modeling based on Recurrent Neural Networks.

Kei Ishida, Masato Kiyama, Ali Ercan, Motoki Amagasaki, Tongbi Tu, Makoto Ueda

CoRR, 2021

2020

Relationship between Recognition Accuracy and Numerical Precision in Convolutional Neural Network Models.

Yasuhiro Nakahara, Masato Kiyama, Motoki Amagasaki, Masahiro Iida

IEICE Trans. Inf. Syst., 2020

2019

A Novel SLM-Based Virtual FPGA Overlay Architecture.

Theingi Myint, Motoki Amagasaki, Qian Zhao, Masahiro Iida, Masato Kiyama

Proceedings of the 13th IEEE International Symposium on Embedded Multicore/Many-core Systems-on-Chip, 2019

Deep Learning Framework with Arbitrary Numerical Precision.

Masato Kiyama, Motoki Amagasaki, Masahiro Iida

Proceedings of the 13th IEEE International Symposium on Embedded Multicore/Many-core Systems-on-Chip, 2019

A Quantized Neural Network Library for Proper Implementation of Hardware Emulation.

Masato Kiyama, Yasuhiro Nakahara, Motoki Amagasaki, Masahiro Iida

Proceedings of the Seventh International Symposium on Computing and Networking Workshops, 2019

2006

Parallel Computations Reveal Hidden Errors of Commonly Used Random Number Generators.

Hyo Ashihara, Ai Kuramoto, Isaku Wada, Makoto Matsumoto, Hironori Kikuchi, Masato Kiyama

Proceedings of the 2006 International Conference on Scientific Computing, 2006

2005

New Method for Dispatching Waiting Logical Processors in Virtual Machine Systems.

Hidenori Umeno, Masato Kiyama, Takafumi Fukunaga, Takashige Kubo

Proceedings of the 29th Annual International Computer Software and Applications Conference, 2005