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

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 …

It is very crucial to identify the intensity of tropical cyclone (TC) accurately. In this article, a
novel TC intensity estimation method is proposed to estimate the TC intensity from …

ABSTRACT A consensus-based algorithm for estimating the current intensity of global
tropical cyclones (TCs) from meteorological satellites is described. The method objectively …

A tropical cyclone (TC) is a type of catastrophic weather encountered in the tropical or
subtropical ocean, and it is of great significance to accurately estimate its intensity. Many …

Tropical cyclones are one of the costliest natural disasters globally because of the wide
range of associated hazards. Thus, an accurate diagnostic model for tropical cyclone …

This article proposes a two-branch convolutional neural network model (TCIENet) to
estimate the intensity of tropical cyclone (TC) from infrared and water vapor images in the …

Existing techniques for satellite-based tropical cyclone (TC) intensity estimation involve an
explicit feature extraction step to model TC intensity on a set of relevant TC features or …

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) …