Machine Learning in Precision Agriculture: A Survey on Trends, Applications and Evaluations Over Two Decades-Reference-Cited by-同舟云学术

Machine Learning in Precision Agriculture: A Survey on Trends, Applications and Evaluations Over Two Decades

Author:

Condran Sarah¹^ORCID,Bewong Michael¹^ORCID,Islam Md Zahidul²,Maphosa Lancelot³,Zheng Lihong¹^ORCID

Affiliation:

1. School of Computing, Mathematics and Engineering, Charles Sturt University, Wagga Wagga, NSW, Australia

2. School of Computing, Mathematics and Engineering, Charles Sturt University, Bathurst, NSW, Australia

3. NSW Department of Primary Industries, Wagga Wagga, NSW, Australia

Funder

Charles Sturt University

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering

Link

Reference182 articles.

1. Benchmarking deep learning interpretability in time series predictions;ismail;Proc Adv Neural Inf Process Syst (NeurIPS),2020

3. A benchmark for interpretability methods in deep neural networks;hooker;Proc Adv Neural Inf Process Syst (NeurIPS),2019

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