Classifying early apple scab infections in multispectral imagery using convolutional neural networks
Multispectral imaging systems combined with deep learning classification models can be cost-effective tools for the early detection of apple scab (Venturia inaequalis) disease in commercial orchards. Near-infrared (NIR) imagery can display apple scab symptoms earlier and at a greater severity than v...
Saved in:
Main Authors: | Alexander J. Bleasdale, J. Duncan Whyatt |
---|---|
Format: | Article |
Language: | English |
Published: |
KeAi Communications Co., Ltd.
2025-03-01
|
Series: | Artificial Intelligence in Agriculture |
Subjects: | |
Online Access: | http://www.sciencedirect.com/science/article/pii/S2589721724000357 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Selection of promising apple genotypes for columnar growth habit and scab resistance using diagnostic DNA markers
by: N. I. Savel’ev, et al.
Published: (2016-08-01) -
The development of triploid apple cultivars is a priority in breeding
by: E. N. Sedov, et al.
Published: (2017-04-01) -
A Classifier Model Using Fine-Tuned Convolutional Neural Network and Transfer Learning Approaches for Prostate Cancer Detection
by: Murat Sarıateş, et al.
Published: (2024-12-01) -
Niedzwetzky’s apple (Malus niedzwetzkyana Dieck): evaluation and breeding prospects
by: O. N. Barsukova
Published: (2020-10-01) -
2018–2019 Florida Citrus Pest Management Guide: Citrus Scab
by: Megan M. Dewdney
Published: (2018-08-01)