Cyclone Intensity Estimation on INSAT 3D IR Imagery Using Deep Learning-Reference-Cited by-同舟云学术

Cyclone Intensity Estimation on INSAT 3D IR Imagery Using Deep Learning

Published:2023-03-14 Issue: Volume: Page:
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Container-title:2023 International Conference on Innovative Data Communication Technologies and Application (ICIDCA)
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Author:

Vayadande Kuldeep¹,Adsare Tejas¹,Dharmik Tejas¹,Agrawal Neeraj¹,Patil Aishwarya¹,Zod Sakshi¹

Affiliation:

1. Vishwakarma Institute of Tecnology,Pune,India

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10099475/10099489/10099964.pdf?arnumber=10099964

Reference23 articles.

1. A Semi Supervised Deep Learning Framework for Tropical Cyclone Intensity Estimation;zhao;2019 10th International Workshop on the Analysis of Multitemporal Remote Sensing Images (MultiIemp),0

2. Tropical Cyclone Intensity Estimation from Geostationary Satellite Imagery Using Deep Convolutional Neural Networks;wang;IEEE Transactions on Geoscience and Remote Sensing,2021

3. Heart Disease Prediction using Machine Learning and Deep Learning Algorithms

4. ImageNet classification with deep convolutional neural networks

5. A Semi supervised Deep Learning Framework for Tropical Cyclone Intensity Estimation;chen;2019 10th International Workshop on the Analysis of Multitemporal Remote Sensing Images (MultiIemp),0

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