Yu Mo

Orcid: 0000-0002-3374-4124

According to our database1, Yu Mo authored at least 14 papers between 2015 and 2024.

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

Timeline

Legend:

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Article 
PhD thesis 
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Links

On csauthors.net:

Bibliography

2024
Feature Extraction Based on Self-Supervised Learning for Remaining Useful Life Prediction.
J. Comput. Inf. Sci. Eng., February, 2024

Semantic-Rearrangement-Based Multi-Level Alignment for Domain Generalized Segmentation.
CoRR, 2024

DAUP: Enhancing point cloud homogeneity for 3D industrial anomaly detection via density-aware point cloud upsampling.
Adv. Eng. Informatics, 2024

2023
Few-shot RUL estimation based on model-agnostic meta-learning.
J. Intell. Manuf., June, 2023

2022
Dense Dual-Attention Network for Light Field Image Super-Resolution.
IEEE Trans. Circuits Syst. Video Technol., 2022

Light Field Angular Super-Resolution via Dense Correspondence Field Reconstruction.
Proceedings of the Computer Vision - ECCV 2022 Workshops, 2022

2021
Salt Marsh Elevation Limit Determined after Subsidence from Hydrologic Change and Hydrocarbon Extraction.
Remote. Sens., 2021

Remaining useful life estimation via transformer encoder enhanced by a gated convolutional unit.
J. Intell. Manuf., 2021

Data-driven hospital personnel scheduling optimization through patients prediction.
CCF Trans. Pervasive Comput. Interact., 2021

2019
Toward Real-World Light Field Depth Estimation: A Noise-Aware Paradigm Using Multi-Stereo Disparity Integration.
IEEE Access, 2019

2018
Disparity Estimation for Camera Arrays Using Reliability Guided Disparity Propagation.
IEEE Access, 2018

2017
Post-Deepwater Horizon Oil Spill Monitoring of Louisiana Salt Marshes Using Landsat Imagery.
Remote. Sens., 2017

2016
A weighted multi-task joint sparse representation method for hyperspectral image classification.
Proceedings of the 2016 IEEE International Geoscience and Remote Sensing Symposium, 2016

2015
Correlating peak NDVIS of salt marshes with environmental conditions in Louisiana, USA, using principal component analysis.
Proceedings of the 2015 IEEE International Geoscience and Remote Sensing Symposium, 2015


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