Abstract: This paper proposes a feature-enhanced parametric Physics-Informed Neural Network (PINNs) to overcome the poor parameter adaptability and high retraining cost of traditional PINNs in ...
Abstract: This study presents a methodology for generating high-quality datasets of samples to train machine learning models for land use and land cover (LULC) classification, representing an initial ...