Development and Optimization of a Novel Deep Learning Model for Diagnosis of Quince Leaf Diseases
IntroductionDetection of tree leaf diseases plays a crucial role in the horticultural field. These diseases can originate from viruses, bacteria, fungi, and other pathogens. If proper attention is not given, these diseases can drastically affect trees, reducing both the quality and quantity of yield...
Saved in:
| Main Authors: | A. Naderi Beni, H. Bagherpour, J. Amiri Parian |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Ferdowsi University of Mashhad
2024-12-01
|
| Series: | Journal of Agricultural Machinery |
| Subjects: | |
| Online Access: | https://jame.um.ac.ir/article_45892_877b70655f8b8844ef3178329498f062.pdf |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Advanced deep transfer learning techniques for efficient detection of cotton plant diseases
by: Prashant Johri, et al.
Published: (2024-12-01) -
Development and application of a cost-effective multiplex Kompetitive Allele-Specific polymerase chain reaction assay for pyramiding resistant genes of fusarium head blight and powdery mildew in wheat
by: Yonggang Wang, et al.
Published: (2025-07-01) -
Median interacted pigeon optimization-based hyperparameter tuning of CNN for paddy leaf disease prediction
by: Jasmy Davies, et al.
Published: (2025-05-01) -
Evaluation of the new antimicrobial benziothiazolinone for management of fire blight disease of pear
by: Jiuxiang Zhu, et al.
Published: (2025-08-01) -
Pear flower and leaf microbiome dynamics during the naturally occurring spread of Erwinia amylovora
by: Aia Oz, et al.
Published: (2025-05-01)