Lin Mu

Orcid: 0000-0002-2966-6370

Affiliations:
  • Shenzhen University, Shenzhen, China


According to our database1, Lin Mu authored at least 14 papers between 2019 and 2022.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

Online presence:

On csauthors.net:

Bibliography

2022
Validation of Wave Spectral Partitions From SWIM Instrument On-Board CFOSAT Against In Situ Data.
IEEE Trans. Geosci. Remote. Sens., 2022

L-UNet: An LSTM Network for Remote Sensing Image Change Detection.
IEEE Geosci. Remote. Sens. Lett., 2022

Improved Transformer Model for Enhanced Monthly Streamflow Predictions of the Yangtze River.
IEEE Access, 2022

A Model Coupling CFD and DRL: Investigation on Wave Dissipation by Actively Controlled Flat Plate.
IEEE Access, 2022

2021
GAN-Based LUCC Prediction via the Combination of Prior City Planning Information and Land-Use Probability.
IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2021

Semantic Segmentation for Buildings of Large Intra-Class Variation in Remote Sensing Images with O-GAN.
Remote. Sens., 2021

2020
Knowledge discovery from remote sensing images: A review.
WIREs Data Mining Knowl. Discov., 2020

Buoy Sensor Cyberattack Detection in Offshore Petroleum Cyber-Physical Systems.
IEEE Trans. Serv. Comput., 2020

Improving Altimeter Wind Speed Retrievals Using Ocean Wave Parameters.
IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2020

Early Prediction of the 2019 Novel Coronavirus Outbreak in the Mainland China Based on Simple Mathematical Model.
IEEE Access, 2020

Streamflow Prediction Using Deep Learning Neural Network: Case Study of Yangtze River.
IEEE Access, 2020

2019
Urban Land Use and Land Cover Change Prediction via Self-Adaptive Cellular Based Deep Learning With Multisourced Data.
IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2019

Hyperspectral Image Denoising With Dual Deep CNN.
IEEE Access, 2019

Security of marine-information system.
Proceedings of the Security and Privacy for Big Data, Cloud Computing and Applications, 2019


  Loading...