Energy-Efficient and Uncertainty-Aware Biomass Composition Prediction on Resource-Constrained Edge Devices

A hybrid approach that leverages both pruned and unpruned deep learning models to enable energy-efficient and accurate biomass composition prediction on resource-constrained edge devices.