Deep Learning and Wavelet Transform Combined With Multichannel Satellite Images for Tropical Cyclone Intensity Estimation
Tropical cyclone (TC) is a highly catastrophic weather event, and accurate estimation of intensity is of great significance. The current proposed TC intensity estimation model focuses on training using satellite images from single or two channels, and the model cannot fully capture features related...
Saved in:
Main Authors: | Chang-Jiang Zhang, Mei-Shu Chen, Lei-Ming Ma, Xiao-Qin Lu |
---|---|
Format: | Article |
Language: | English |
Published: |
IEEE
2025-01-01
|
Series: | IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/10845190/ |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Tropical cyclone intensity estimation based on YOLO-NAS using satellite images in real time
by: Priyanka Nandal, et al.
Published: (2025-02-01) -
Modulation of western North Pacific tropical cyclone decadal variability by the Victoria mode
by: Tao Wen, et al.
Published: (2025-01-01) -
Improving tropical cyclone rapid intensification forecasts with satellite measurements of sea surface salinity and calibrated machine learning
by: Ryan Eusebi, et al.
Published: (2025-01-01) -
Simulation of an intense tropical cyclone in the conformal cubic atmospheric model and its sensitivity to horizontal resolutionhttps://cds.climate.copernicus.eu/
by: Son C. H. Truong, et al.
Published: (2025-03-01) -
Norm Retrievable Wavelet Systems
by: Mahdieh sadat Aghaei, et al.
Published: (2024-10-01)