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Empowering Precision Agriculture: A Novel ResNet50 based PDICNet for Automated Apple Leaf Disease De...

Empowering Precision Agriculture: A Novel ResNet50 based PDICNet for Automated Apple Leaf Disease De...

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_journals_3081859622

Empowering Precision Agriculture: A Novel ResNet50 based PDICNet for Automated Apple Leaf Disease Detection

About this item

Full title

Empowering Precision Agriculture: A Novel ResNet50 based PDICNet for Automated Apple Leaf Disease Detection

Publisher

Paris: Engineering and Scientific Research Groups

Journal title

Journal of Electrical Systems, 2024-05, Vol.20 (7s), p.2211-2220

Language

English

Formats

Publication information

Publisher

Paris: Engineering and Scientific Research Groups

More information

Scope and Contents

Contents

Inspection of plant leaves through the naked eye is difficult and does not guarantee accurate assessment which results in economic loss to the farmers. Biotic or abiotic stress develop lesions on plant leaves and reduce crop quality and yield. This paper presents a novel model that uses RestNet50-based Deep Learning Convolutional Neural Network (DL...

Alternative Titles

Full title

Empowering Precision Agriculture: A Novel ResNet50 based PDICNet for Automated Apple Leaf Disease Detection

Authors, Artists and Contributors

Identifiers

Primary Identifiers

Record Identifier

TN_cdi_proquest_journals_3081859622

Permalink

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_journals_3081859622

Other Identifiers

E-ISSN

1112-5209

DOI

10.52783/jes.3956

How to access this item