no code implementations • 13 Jul 2022 • Takato Yasuno, Junichiro Fujii, Masazumi Amakata
We propose a patch-wise classification pipeline to detect scum features on the river surface using mixture image augmentation to increase the diversity between the scum floating on the river and the entangled background on the river surface reflected by nearby structures like buildings, bridges, poles, and barriers.
no code implementations • 6 Dec 2021 • Takato Yasuno, Masazumi Amakata, Junichiro Fujii, Masahiro Okano, Riku Ogata
It is important to forecast dam inflow for flood damage mitigation.
no code implementations • 14 Jan 2021 • Takato Yasuno, Junichiro Fujii, Hiroaki Sugawara, Masazumi Amakata
Based on these trained networks, we automatically compute the road to snow rate hazard index, indicating the amount of snow covered on the road surface.
no code implementations • 30 Sep 2020 • Takato Yasuno, Akira Ishii, Masazumi Amakata
Spatiotemporal precipitation forecasts may enhance the accuracy of dam inflow prediction, more than 6 hours forward for flood damage mitigation.
no code implementations • 27 Jun 2020 • Takato Yasuno, Akira Ishii, Junichiro Fujii, Masazumi Amakata, Yuta Takahashi
When a damaged image is a generator input, it tends to reverse from the damaged state to the healthy state generated image.
no code implementations • 21 Apr 2020 • Takato Yasuno, Masazumi Amakata, Masahiro Okano
This paper proposes a practical method to visualize the damaged areas focused on the typhoon disaster features using aerial photography.