Deep Learning (DL), a subset of Machine Learning (ML), has emerged as a powerful tool in environmental science, reshaping the landscape of data analysis and interpretation. This study focuses on the remarkable impact of DL on various aspects of environmental science, including remote sensing, climate modelling, biodiversity assessment, pollution monitoring, and environmental health.

Magazzino, C. (2024). The impact of deep learning on environmental science. BMC ENVIRONMENTAL SCIENCE, 1(4) [10.1186/s44329-024-00003-5].

The impact of deep learning on environmental science

Magazzino, Cosimo
2024-01-01

Abstract

Deep Learning (DL), a subset of Machine Learning (ML), has emerged as a powerful tool in environmental science, reshaping the landscape of data analysis and interpretation. This study focuses on the remarkable impact of DL on various aspects of environmental science, including remote sensing, climate modelling, biodiversity assessment, pollution monitoring, and environmental health.
2024
Magazzino, C. (2024). The impact of deep learning on environmental science. BMC ENVIRONMENTAL SCIENCE, 1(4) [10.1186/s44329-024-00003-5].
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11590/476687
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus ND
  • ???jsp.display-item.citation.isi??? ND
social impact