Forecasting risk of crop disease with anomaly detection algorithms.

Research output: Contribution to journal › Article › peer-review

Keywords

@article{7301535f05944a529aa5ad77f05db548,

title = "Forecasting risk of crop disease with anomaly detection algorithms.",

keywords = "Anomaly detection, Crops, Decision support, Disease, Machine learning",

author = "P. Skelsey",

year = "2021",

month = feb,

day = "1",

doi = "10.1094/PHYTO-05-20-0185-R",

language = "English",

volume = "111",

pages = "321--332",

journal = "Phytopathology",

number = "2",

}

TY - JOUR

T1 - Forecasting risk of crop disease with anomaly detection algorithms.

AU - Skelsey, P.

PY - 2021/2/1

Y1 - 2021/2/1

KW - Anomaly detection

KW - Crops

KW - Decision support

KW - Disease

KW - Machine learning

U2 - 10.1094/PHYTO-05-20-0185-R

DO - 10.1094/PHYTO-05-20-0185-R

M3 - Article

VL - 111

SP - 321

EP - 332

JO - Phytopathology

JF - Phytopathology

IS - 2

ER -