An Efficient Encoding Spectral Information in Hyperspectral Images for Transfer Learning of Mask R-CNN for Instance Segmentation of Tomato Sepals
- DOI
- 10.1109/access.2025.3569213
- Published
- 2025
- Container
- IEEE Access
- Publisher
- Institute of Electrical and Electronics Engineers (IEEE)
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1109/access.2025.3569213,
title = {An Efficient Encoding Spectral Information in Hyperspectral Images for Transfer Learning of Mask R-CNN for Instance Segmentation of Tomato Sepals},
author = {Željana Grbović and Marko Panić and Vladan Filipović and Sanja Brdar and Hendrik de Villiers and Manon Mensink and Aneesh Chauhan},
year = {2025},
journal = {IEEE Access},
doi = {10.1109/access.2025.3569213},
url = {https://doi.org/10.1109/access.2025.3569213}
}RIS
TY - JOUR TI - An Efficient Encoding Spectral Information in Hyperspectral Images for Transfer Learning of Mask R-CNN for Instance Segmentation of Tomato Sepals AU - Željana Grbović AU - Marko Panić AU - Vladan Filipović AU - Sanja Brdar AU - Hendrik de Villiers AU - Manon Mensink AU - Aneesh Chauhan PY - 2025 JO - IEEE Access DO - 10.1109/access.2025.3569213 UR - https://doi.org/10.1109/access.2025.3569213 ER -
APA
Grbović, Ž., Panić, M., Filipović, V., Brdar, S., Villiers, H. D., Mensink, M., & Chauhan, A. (2025). An Efficient Encoding Spectral Information in Hyperspectral Images for Transfer Learning of Mask R-CNN for Instance Segmentation of Tomato Sepals. IEEE Access. https://doi.org/10.1109/access.2025.3569213
Source records
- crossref · retrieved 2026-09-26T11:21:56.921Z