A Disentangled Variational Autoencoder for Prediction of Above Ground Biomass from Hyperspectral Data. - Parth Naik; Michele Dalponte; Lorenzo Bruzzone (IGARSS, 2021)

Prediction of Forest Aboveground Biomass Using Multitemporal Multispectral Remote Sensing Data. - Parth Naik; Michele Dalponte; Lorenzo Bruzzone (Remote. Sens., 2021)

Generative Feature Extraction From Sentinel 1 and 2 Data for Prediction of Forest Aboveground Biomass in the Italian Alps. - Parth Naik; Michele Dalponte; Lorenzo Bruzzone (IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2022)

Automated Machine Learning Driven Stacked Ensemble Modeling for Forest Aboveground Biomass Prediction Using Multitemporal Sentinel-2 Data. - Parth Naik; Michele Dalponte; Lorenzo Bruzzone (IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2023)

Integrating Airborne and Satellite Hyperspectral Data for Enhanced Spectral Unmixing. - Rupsa Chakraborty; Samuel T. Thiele; Parth Naik; Moritz Kirsch; Richard Gloaguen (WHISPERS, 2024)

Multi-Objective Optimization Based Hyperspectral Feature Engineering for Spectral Abundance Mapping. - Parth Naik; Rupsa Chakraborty; Sam Thiele; Moritz Kirsch; Richard Gloaguen (WHISPERS, 2024)