Tropical cyclone intensity estimation is a challenging task as it required domain knowledge
while extracting features, significant pre-processing, various sets of parameters obtained …

Abadi, M., and Coauthors, 2016: TensorFlow: A system for large-scale machine learning.
Proc. 12th USENIX Conf. on Operating Systems Design and Implementation, Savannah, GA …

In this study, a set of deep convolutional neural networks (CNNs) was designed for
estimating the intensity of tropical cyclones (TCs) over the Northwest Pacific Ocean from the …

A novel tropical cyclone (TC) intensity classification and estimation model (TCICENet) is
proposed using infrared geostationary satellite images from the northwest Pacific Ocean …

For a long time, researchers have tried to find a way to analyze tropical cyclone (TC)
intensity in real-time. Since there is no standardized method for estimating TC intensity and …

Estimating Tropical Cyclone Intensity by Satellite Imagery Utilizing Convolutional Neural
Networks in: Weather and Forecasting Volume 34 Issue 2 (2019) Jump to Content Jump to Main …

Tropical cyclones (TCs) seriously endanger human life and the safety of property. Real-time
monitoring of TCs has been one of the focal points in meteorological studies. With the …

Tropical cyclone (TC) is a type of severe weather systems that occur in tropical regions.
Accurate estimation of TC intensity is crucial for disaster management. Moreover, the …

In this report, we propose a deep learning technique for high-accuracy estimation of the
intensity class of a typhoon from a single satellite image, by incorporating meteorological …

This study develops an objective deep-learning-based model for tropical cyclone (TC)
intensity estimation. The model's basic structure is a convolutional neural network (CNN) …