Motoki Amagasaki

Capabilities of deep learning models on learning physical relationships: Case of rainfall-runoff modeling with LSTM

Kazuki Yokoo, Kei Ishida, Ali Ercan et al. · The Science of The Total Environment · 2021 · 57 citations · Full text

Convolutional Neural Network, Deep Neural Networks, Engineering +9

Improving the Robustness of a Softcore Processor against SEUs by Using TMR and Partial Reconfiguration

Yoshihiro Ichinomiya, Shiro Tanoue, Motoki Amagasaki et al. · 2010 · 55 citations

Engineering, Computer Architecture, Embedded Systems +20

Hourly-scale coastal sea level modeling in a changing climate using long short-term memory neural network

Kei Ishida, Gozo TSUJIMOTO, Ali Ercan et al. · The Science of The Total Environment · 2020 · 48 citations

Climatology, Meteorology, Coastal Management +10

Use of one-dimensional CNN for input data size reduction in LSTM for improved computational efficiency and accuracy in hourly rainfall-runoff modeling

Kei Ishida, Ali Ercan, Takeyoshi Nagasato et al. · Journal of Environmental Management · 2024 · 40 citations · Full text

Hydrometeorology, Convolutional Neural Network, Recurrent Neural Network +9

Super-resolution of sea surface temperature with convolutional neural network- and generative adversarial network-based methods

Tomoki Izumi, Motoki Amagasaki, Kei Ishida et al. · Journal of Water and Climate Change · 2022 · 35 citations · Full text

Convolutional Neural Network, Engineering, Machine Learning +16