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
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
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