Jizhen Cai
Country of Origin: China
Host Institution: C2RMF
jizhen.cai@culture.gouv.fr
Background:
Jizhen completed the master of science in Simulation and Visualization in NTNU (Norwegian University of Science and Technology). His interests include Data Processing, Machine Learning and Deep Learning.
Aspirations within projects:
In this project, Jizhen believes his knowledge and skills in data processing and visualization would be quite helpful. Additionally, he is looking forward to cooperating with other researchers within this exciting CHANGE project.
ESR6: Development of multi modal image data fusion methods for change monitoring
Objectives
- Identify data representations and cross-analysis with heterogeneous multi modal inputs available at the museums- 2D (e.g., spectral, fluoX, and chemical imaging).
- Visualization of data from heterogeneous sources.
- Construct data fusion model with computing analysis and other information as object historical data for restoration.
- Use of the change monitoring methods to analyse paintings and statues at the Louvre museum.
Main Supervisor:
- Clotilde Boust (C2RMF)
Co-Supervisor(s):
- Alamin Mansouri (UBFC)
- Hermine Chatoux (UBFC)
Cai, J., H. Chatoux, C. Boust, A. Mansouri (2021). Extending the Unmixing methods to Multispectral Images. 29th Color and Imaging Conference Final Program and Proceedings, pp. 311-316(6). Society for Imaging Science and Technology. https://doi.org/10.2352/issn.2169-2629.2021.29.311
Cai, J., H. Chatoux, C. Boust, A. Mansouri (2021): Comparison of Linear Unmixing Methods on Paintings Data Set. ORASIS 2021, Centre National de la Recherche Scientifique [CNRS], Sep 2021, Saint Ferréol, France. ffhal-03339685f.