An Efficient Encoding Spectral Information in Hyperspectral Images for Transfer Learning of Mask R-CNN for Instance Segmentation of Tomato Sepals

An Efficient Encoding Spectral Information in Hyperspectral Images for Transfer Learning of Mask R-CNN for Instance Segmentation of Tomato Sepals

The most vulnerable parts of tomatoes are the tips of the sepals, which are the primary entry points for fungal spores. Their precise segmentation within hyperspectral images (HSIs) plays a pivotal role in the development of automated and non-destructive systems for assessing tomatoes’ se...

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Bibliographic Details
Main Authors: Zeljana Grbovic, Marko Panic, Vladan Filipovic, Sanja Brdar, Hendrik de Villiers, Manon Mensink, Aneesh Chauhan
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
Subjects:
Hyperspectral imaging (HSI)
encoding spectral information in HSI
deep learning
transfer learning
instance segmentation
tomato
Online Access:https://ieeexplore.ieee.org/document/11000115/
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