North Indian Ocean Tropical Cyclone Detection Using YOLOv5

Abstract

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 of the most devastating natural disasters that cause significant loss of lives and property damage. Accurate and timely detection and classification of cyclones can help in effective disaster management and mitigation. In this study, YOLOv5 is used for detecting and classifying cyclones in satellite images. The proposed method involves pre-processing the data, training the YOLOv5 model on the dataset, and evaluating the model's performance. The results demonstrate that the proposed method achieved high accuracy in both cyclone detection and classification tasks. This research paper provides insights into the potential of YOLOv5 in cyclone detection and classification, which can be beneficial in enhancing disaster management strategies. © 2024 IEEE.