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ArticlesPeer ReviewedFull Text
Super-resolution of sea surface temperature with convolutional neural network- and generative adversarial network-based methods
Author / Creator:Izumi, Tomoki ; Amagasaki, Motoki ; Ishida, Kei ; Kiyama, Masato
Publisher:London: IWA Publishing
Journal title:Journal of water and climate change, 2022-04, Vol.13 (4), p.1673-1683
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ArticlesPeer ReviewedFull Text
Multimodal Retrieval Method for Images and Diagnostic Reports Using Cross-Attention
Author / Creator:Sata, Ikumi ; Amagasaki, Motoki ; Kiyama, Masato
Publisher:Basel: MDPI AG
Journal title:AI (Basel), 2025-02, Vol.6 (2), p.38
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ArticlesPeer ReviewedFull Text
Optimizing AI models to predict esophageal squamous cell carcinoma risk by incorporating small datasets of soft palate images
Author / Creator:Waki, Kotaro ; Nagaoka, Katsuya ; Okubo, Keishi ; Kiyama, Masato ; Gushima, Ryosuke ; Ohno, Kento ; Honda, Munenori ; Yamasaki, Akira ; Matsuno, Kenshi ; Furuta, Yoki ; Miyamoto, Hideaki ; Naoe, Hideaki ; Amagasaki, Motoki ; Tanaka, Yasuhito
Publisher:London: Nature Publishing Group UK
Journal title:Scientific reports, 2025-02, Vol.15 (1), p.4003-11, Article 4003
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ArticlesPeer ReviewedFull Text
Multi-time-scale input approaches for hourly-scale rainfall–runoff modeling based on recurrent neural networks
Author / Creator:Ishida, Kei ; Kiyama, Masato ; Ercan, Ali ; Amagasaki, Motoki ; Tu, Tongbi
Publisher:London: IWA Publishing
Journal title:Journal of hydroinformatics, 2021-11, Vol.23 (6), p.1312-1324
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ArticlesPeer ReviewedFull Text
Multi-Agent Reinforcement Learning-Based Control Method for Pedestrian Guidance Using the Mojiko Fireworks Festival Dataset
Author / Creator:Kiyama, Masato ; Amagasaki, Motoki ; Okamoto, Toshiaki
Publisher:Basel: MDPI AG
Journal title:Electronics (Basel), 2025-03, Vol.14 (6), p.1062
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ArticlesFull Text
Multi-Time-Scale Input Approaches for Hourly-Scale Rainfall-Runoff Modeling based on Recurrent Neural Networks
Author / Creator:Ishida, Kei ; Kiyama, Masato ; Ercan, Ali ; Amagasaki, Motoki ; Tu, Tongbi
Publisher:Ithaca: Cornell University Library, arXiv.org
Journal title:arXiv.org, 2021-11
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ArticlesFull Text
Capabilities of Deep Learning Models on Learning Physical Relationships: Case of Rainfall-Runoff Modeling with LSTM
Author / Creator:Yokoo, Kazuki ; Ishida, Kei ; Ercan, Ali ; Tu, Tongbi ; Nagasato, Takeyoshi ; Kiyama, Masato ; Amagasaki, Motoki
Publisher:Ithaca: Cornell University Library, arXiv.org
Journal title:arXiv.org, 2021-11
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ArticlesFull Text
Development of Quantized DNN Library for Exact Hardware Emulation
Author / Creator:Kiyama, Masato ; Amagasaki, Motoki ; Iida, Masahiro
Publisher:Ithaca: Cornell University Library, arXiv.org
Journal title:arXiv.org, 2021-06
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ArticlesFull Text
Use of 1D-CNN for input data size reduction of LSTM in Hourly Rainfall-Runoff modeling
Author / Creator:Ishida, Kei ; Ercan, Ali ; Nagasato, Takeyoshi ; Kiyama, Masato ; Amagasaki, Motoki
Publisher:Ithaca: Cornell University Library, arXiv.org
Journal title:arXiv.org, 2021-11
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ArticlesFull Text
Extension of Convolutional Neural Network along Temporal and Vertical Directions for Precipitation Downscaling
Author / Creator:Nagasato, Takeyoshi ; Ishida, Kei ; Ercan, Ali ; Tu, Tongbi ; Kiyama, Masato ; Amagasaki, Motoki ; Yokoo, Kazuki
Publisher:Ithaca: Cornell University Library, arXiv.org
Journal title:arXiv.org, 2021-12
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Super-resolution of sea surface temperature with convolutional neural network- and generative adversarial network-based methods

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Multimodal Retrieval Method for Images and Diagnostic Reports Using Cross-Attention

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Optimizing AI models to predict esophageal squamous cell carcinoma risk by incorporating small datasets of soft palate images

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Multi-time-scale input approaches for hourly-scale rainfall–runoff modeling based on recurrent neural networks

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Multi-Agent Reinforcement Learning-Based Control Method for Pedestrian Guidance Using the Mojiko Fireworks Festival Dataset

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

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

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Development of Quantized DNN Library for Exact Hardware Emulation

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

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

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