28 citations · 33 across the 4 of their papers we have counts for
4 papers
Insight into cloud processes from unsupervised classification with a rotationally invariant autoencoder
Takuya Kurihana, James Franke, Ian Foster +2
Clouds play a critical role in the Earth's energy budget and their potential changes are one of the largest uncertainties in future climate projections. However, the use of satelli…
Cloud Classification with Unsupervised Deep Learning
Takuya Kurihana, Ian Foster, Rebecca Willett +6
We present a framework for cloud characterization that leverages modern unsupervised deep learning technologies. While previous neural network-based cloud classification models hav…
AICCA: AI-driven Cloud Classification Atlas
Takuya Kurihana, Elisabeth Moyer, Ian Foster
Clouds play an important role in the Earth's energy budget and their behavior is one of the largest uncertainties in future climate projections. Satellite observations should help…
Data-driven Cloud Clustering via a Rotationally Invariant Autoencoder
Takuya Kurihana, Elisabeth Moyer, Rebecca Willett +2
Advanced satellite-born remote sensing instruments produce high-resolution multi-spectral data for much of the globe at a daily cadence. These datasets open up the possibility of i…