Recently, deep learning (DL) has emerged as a revolutionary and versatile tool transforming
industry applications and generating new and improved capabilities for scientific discovery …

The advent of technology including big data has allowed machine learning technology to
strengthen its place in solving different science and engineering complex problems …

We propose a deep learning approach for identifying tropical cyclones (TCs) and their
precursors. Twenty year simulated outgoing longwave radiation (OLR) calculated using a …

Accurate detection of tropical cyclones (TCs) is important to prevent and mitigate natural
disasters associated with TCs. Deep transfer learning methods have advantages in …

Tropical cloud clusters (TCCs) can potentially develop into tropical cyclones (TCs), leading
to significant casualties and economic losses. Accurate prediction of tropical cyclogenesis …

Deep Learning (DL) models for semantic image segmentation are an emerging trend in
response to the explosion of multi-class, high resolution image and video data. However …

Recently, deep learning (DL) has emerged as a revolutionary and versatile tool transforming
industry applications and generating new and improved capabilities for scientific discovery …

Complete meteorological data is essential for meteorological research. However, due to
sensor failure or occlusion, data loss always occurs. In order to deal with this problem …

Tropical cyclones (TC) harm both people and property over coastal regions, so early
estimation of the TC intensity can help reduce the damage. Intensity estimation of a tropical …

This research paper focuses on the application of You Only Look Once version 5 (YOLOv5)
Deep Learning (DL) architecture for cyclone detection and classification. Cyclones are one …