Trigonometric-Euclidean-Smoother Interpolator (TESI) for continuous time-series and non-time-series data augmentation for deep neural network applications in agriculture
Biomass estimation, fertilisation, and crop production reflect crop yield potential. The prediction of these variables allows the selection of crop cultivars with high yield potential. Deep neural networks (DNNs) can predict such crop variables. However, DNNs are data greedy algorithms that overfit/...
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| Main Authors: | , , , |
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| Format: | Article |
| Published: |
Elsevier
2023
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| Online Access: | http://psasir.upm.edu.my/id/eprint/108355/ https://www.sciencedirect.com/science/article/abs/pii/S0168169923000340?via%3Dihub |
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