Automated deep learning
An automated soil sensing platform to analyze many soil properties.
Deep learning models usually come with a large number of hyperparameters, and their selection is critical for their performance. To find the set of hyperparameters that generates optimal model performance, one needs to employ hyperparameter tuning, or optimisation (HPO).
This project developed HPO with Bayesian optimisation for the automated hyperparameter tunning for convolutional neural networks (CNN) (Shen & Viscarra Rossel, 2021).