Yaping Cai

Orcid: 0000-0002-8608-3454

According to our database1, Yaping Cai authored at least 12 papers between 2016 and 2023.

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

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
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Links

On csauthors.net:

Bibliography

2023
Correction: Lin et al. Toward Large-Scale Mapping of Tree Crops with High-Resolution Satellite Imagery and Deep Learning Algorithms: A Case Study of Olive Orchards in Morocco. Remote Sens. 2021, 13, 1740.
Remote. Sens., January, 2023

2021
Evaluation of Four New Land Surface Temperature (LST) Products in the U.S. Corn Belt: ECOSTRESS, GOES-R, Landsat, and Sentinel-3.
IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2021

Toward Large-Scale Mapping of Tree Crops with High-Resolution Satellite Imagery and Deep Learning Algorithms: A Case Study of Olive Orchards in Morocco.
Remote. Sens., 2021

2020
Double-Line Frequency Ripple Suppression of a Quasi-Single Stage AC-DC Converter.
IEEE Trans. Circuits Syst. II Express Briefs, 2020

Spatiotemporal Derivation of Intermittent Ponding in a Maize-Soybean Landscape from Planet Labs CubeSat Images.
Remote. Sens., 2020

Similarity Measurement Based on Non-linear Hash Coding.
Proceedings of the CSAE 2020: The 4th International Conference on Computer Science and Application Engineering, 2020

Learning to Rank for Blind Image Quality Assessment.
Proceedings of the CSAE 2020: The 4th International Conference on Computer Science and Application Engineering, 2020

2019
Evaluation and Suppression of a Low-Frequency Output Voltage Ripple of a Single-Stage AC-DC Converter Based on an Output Impedance Model.
IEEE Trans. Ind. Electron., 2019

Design of Double-Line-Frequency Ripple Controller for Quasi-Single-Stage AC-DC Converter With Audio Susceptibility Model.
IEEE Trans. Ind. Electron., 2019

Detecting In-Season Crop Nitrogen Stress of Corn for Field Trials Using UAV- and CubeSat-Based Multispectral Sensing.
IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2019

A spatiotemporal deep learning model for sea surface temperature field prediction using time-series satellite data.
Environ. Model. Softw., 2019

2016
Data depth based clustering analysis.
Proceedings of the 24th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, GIS 2016, Burlingame, California, USA, October 31, 2016


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