Trigonometric-Euclidean-Smoother Interpolator (TESI) for continuous time-series and non-time-series data augmentation for deep neural network applications in agriculture

• Main Authors: Derraz, Radhwane, Muharam, Farrah Melissa, Jaafar, Noraini Ahmad, Yap, Ng Keng
• Format: Article
• Published: Elsevier 2023
• Online Access: http://psasir.upm.edu.my/id/eprint/108355/; https://www.sciencedirect.com/science/article/abs/pii/S0168169923000340?via%3Dihub

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/...