AI assists in locating hidden farms
Francesc X. Prenafeta-Boldú () and
Andreas Kamilaris ()
Additional contact information
Francesc X. Prenafeta-Boldú: Program of Integral Management of Organic Waste, Institute of Agrifood Research and Technology (GIRO-IRTA)
Andreas Kamilaris: Program of Integral Management of Organic Waste, Institute of Agrifood Research and Technology (GIRO-IRTA)
Nature Sustainability, 2019, vol. 2, issue 4, 262-263
Abstract:
In many countries, it is difficult for government agencies to know where animal farms are located. Using satellite imaging and deep learning provides a new, effective, accurate and low-cost approach for detecting these facilities.
Date: 2019
References: Add references at CitEc
Citations: View citations in EconPapers (1)
Downloads: (external link)
https://www.nature.com/articles/s41893-019-0264-8 Abstract (text/html)
Access to the full text of the articles in this series is restricted.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:nat:natsus:v:2:y:2019:i:4:d:10.1038_s41893-019-0264-8
Ordering information: This journal article can be ordered from
https://www.nature.com/natsustain/
DOI: 10.1038/s41893-019-0264-8
Access Statistics for this article
Nature Sustainability is currently edited by Monica Contestabile
More articles in Nature Sustainability from Nature
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().