ResNet-Locust-BN Network-Based Automatic Identification of East Asian Migratory Locust Species and Instars from RGB Images.

CNN deep learning grasshopper image processing locust monitoring and forecasting

Journal

Insects
ISSN: 2075-4450
Titre abrégé: Insects
Pays: Switzerland
ID NLM: 101574235

Informations de publication

Date de publication:
22 Jul 2020
Historique:
received: 13 05 2020
revised: 25 06 2020
accepted: 17 07 2020
entrez: 26 7 2020
pubmed: 28 7 2020
medline: 28 7 2020
Statut: epublish

Résumé

Locusts are agricultural pests found in many parts of the world. Developing efficient and accurate locust information acquisition techniques helps in understanding the relation between locust distribution density and structural changes in locust communities. It also helps in understanding the hydrothermal and vegetation growth conditions that affect locusts in their habitats in various parts of the world as well as in providing rapid and accurate warnings on locust plague outbreak. This study is a preliminary attempt to explore whether the batch normalization-based convolutional neural network (CNN) model can be applied used to perform automatic classification of East Asian migratory locust (AM locust),

Identifiants

pubmed: 32707761
pii: insects11080458
doi: 10.3390/insects11080458
pmc: PMC7469226
pii:
doi:

Types de publication

Journal Article

Langues

eng

Références

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pubmed: 22875984
IEEE Trans Pattern Anal Mach Intell. 2017 Jan;39(1):128-140
pubmed: 26955014
Nat Commun. 2014;5:2957
pubmed: 24423660
Insects. 2019 Mar 01;10(3):
pubmed: 30832259
J Environ Manage. 2018 Jul 15;218:280-290
pubmed: 29684780
Annu Rev Entomol. 2019 Jan 7;64:15-34
pubmed: 30256665

Auteurs

Sijing Ye (S)

State Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing Normal University, Beijing 100875, China.
Center for Geodata and Analysis, Beijing Normal University, Beijing 100875, China.

Shuhan Lu (S)

Master of Health Informatics, School of Information, University of Michigan, Ann Arbor, MI 48109, USA.

Xuesong Bai (X)

Key Laboratory of Agricultural Land Quality (Beijing) Ministry of Land and Resources, China Agricultural University, Beijing 100083, China.

Jinfeng Gu (J)

Key Laboratory of Agricultural Land Quality (Beijing) Ministry of Land and Resources, China Agricultural University, Beijing 100083, China.

Classifications MeSH