Estimating Chlorophyll Content from Hyperspectral Data Using Gradient Features
Author:
Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-36021-3_18
Reference19 articles.
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3. Chicco, D., Oneto, L., Tavazzi, E.: Eleven quick tips for data cleaning and feature engineering. PLoS Comput. Biol. 18(12), 1–21 (2022)
4. Gorretta, N., Nouri, M., Herrero, A., Gowen, A., Roger, J.M.: Early detection of the fungal disease “apple scab” using SWIR hyperspectral imaging. In: 2019 10th Workshop on Hyperspectral Imaging and Signal Processing: Evolution in Remote Sensing (WHISPERS), pp. 1–4 (2019)
5. Guo, C., et al.: Predicting Fv/Fm and evaluating cotton drought tolerance using hyperspectral and 1D-CNN. Front. Plant Sci. 13, 3700 (2022)
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