A Lightweight Multitask Learning Model With Adaptive Loss Balance for Tropical Cyclone Intensity and Size Estimation-Reference-Cited by-同舟云学术

A Lightweight Multitask Learning Model With Adaptive Loss Balance for Tropical Cyclone Intensity and Size Estimation

Published:2023 Issue: Volume:16 Page:1057-1071
ISSN:1939-1404
Container-title:IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
language:
Short-container-title:IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

Author:

Tian Wei¹^ORCID,Zhou Xinxin¹^ORCID,Niu Xianhua²,Lai Linhong¹,Zhang Yonghong³,Sian Kenny Thiam Choy Lim Kam⁴^ORCID

Affiliation:

1. School of Computer and Software, Engineering Research Center of Digital Forensics, Ministry of Education, Nanjing University of Information Science and Technology, Nanjing, China

2. State Key Laboratory of Geo-Information Engineering, Xi'an, China

3. School of Automation, Nanjing University of Information Science and Technology, Nanjing, China

4. Wuxi University, Wuxi, China

Funder

National Natural Science Foundation of China

173 National Basic Research Program of China

National Key Research and Development Program of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Atmospheric Science,Computers in Earth Sciences

Link

http://xplorestaging.ieee.org/ielx7/4609443/9973430/09970399.pdf?arnumber=9970399

Reference46 articles.

1. The cimss satellite consensus (SATCON) tropical cyclone intensity algorithm;herndon;Proc 29th Conf Hurricanes Trop Meteorol D,0

2. Tropical cyclone intensity estimation using multi-dimensional convolutional neural network from multi-channel satellite imagery;tian;IEEE Geosci Remote Sens Lett,2021

3. Satellite-Derived Tropical Cyclone Intensity in the North Pacific Ocean Using the Deviation-Angle Variance Technique

4. Physics-augmented Deep Learning to Improve Tropical Cyclone Intensity and Size Estimation from Satellite Imagery

5. An update on the CIMSS satellite consensus (SATCON) tropical cyclone intensity algorithm;velden;Proc Joint Satell Conf,0

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