Profil

WANG Yiqun

University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > SEDAN

ORCID
0000-0001-8459-8334
Main Referenced Co-authors
STATE, Radu  (4)
HUANG, Hui  (3)
LI, Lujun  (1)
Main Referenced Keywords
Crop mapping (2); Cropland data layer (2); cropland data layer (2); Data layer (2); Early crop mapping (2);
Main Referenced Disciplines
Computer science (5)

Publications (total 5)

The most downloaded
144 downloads
WANG, Y. (2024). Cross Domain Early Crop Mapping based on Time-series Remote Sensing Data [Doctoral thesis, The Interdisciplinary Centre for Security, Reliability and Trust (SnT)]. ORBilu-University of Luxembourg. https://orbilu.uni.lu/handle/10993/62970 https://hdl.handle.net/10993/62970

The most cited

7 citations (OpenAlex)

WANG, Y., HUANG, H., & STATE, R. (2023). Early Crop Mapping Using Dynamic Ecoregion Clustering: A USA-Wide Study. Remote Sensing. doi:10.3390/rs15204962 https://hdl.handle.net/10993/57364

LI, L., WANG, Y., & STATE, R. (08 August 2025). Vision Transformer-Based Time-Series Image Reconstruction for Cloud-Filling Applications [Paper presentation]. 2025 IEEE International Geoscience and Remote Sensing Symposium.
Peer reviewed

WANG, Y. (2024). Cross Domain Early Crop Mapping based on Time-series Remote Sensing Data [Doctoral thesis, The Interdisciplinary Centre for Security, Reliability and Trust (SnT)]. ORBilu-University of Luxembourg. https://orbilu.uni.lu/handle/10993/62970

WANG, Y., HUANG, H., & STATE, R. (09 May 2024). Cross Domain Early Crop Mapping with Label Spaces Discrepancies using MultiCropGAN. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, X-1-2024, 241-248. doi:10.5194/isprs-annals-X-1-2024-241-2024
Peer Reviewed verified by ORBi

WANG, Y., HUANG, H., & STATE, R. (2024). Cross Domain Early Crop Mapping Using CropSTGAN. IEEE Access, 12, 130800 - 130815. doi:10.1109/ACCESS.2024.3436620
Peer Reviewed verified by ORBi

WANG, Y., HUANG, H., & STATE, R. (2023). Early Crop Mapping Using Dynamic Ecoregion Clustering: A USA-Wide Study. Remote Sensing. doi:10.3390/rs15204962
Peer Reviewed verified by ORBi

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