Deep Hybrid Learning Framework for Plant Disease Recognition

Ashen Iranga Hewarathna, Vigneshwaran Palanisamy, Joseph Charles, Selvarajah Thuseethan

Research output: Chapter in Book/Report/Conference proceedingConference Paper published in Proceedingspeer-review

Abstract

Following better agricultural practices is the key to catering for the ever-increasing food demand. While new technologies have been adapted over the years, there is still a need for effective plant disease recognition systems because of the existence of harmful plant diseases that can spread rapidly. Effective and early recognition of plant diseases is vital to minimize the damage to crops and hence can save the farmers from potential loss. It is also important for many countries to maintain economic stability, especially for the countries that completely rely on agriculture. In the past, many traditional and deep learning-based approaches have been proposed for plant disease recognition. While traditional approaches need insightful domain expertise, deep learning-based approaches require large sets of labeled data. Further, most of the existing methods fail to meet benchmark performances in terms of recognition accuracy. Therefore, in this study, a novel deep hybrid architecture is proposed to perform plant disease recognition from plant leave images. The Google Inception and ResNet architectures are utilized as the core networks to construct the proposed network. The proposed framework is evaluated on a newly constructed dataset with large sample size. The comparative analysis reveals that the proposed approach can outperform other state-of-the-art deep networks.

Original languageEnglish
Title of host publicationProceedings - International Research Conference on Smart Computing and Systems Engineering, SCSE 2022
PublisherIEEE, Institute of Electrical and Electronics Engineers
Pages49-54
Number of pages6
ISBN (Electronic)9781665473750
DOIs
Publication statusPublished - 2022
Event2022 International Research Conference on Smart Computing and Systems Engineering, SCSE 2022 - Colombo, Sri Lanka
Duration: 1 Sept 2022 → …

Publication series

NameProceedings - International Research Conference on Smart Computing and Systems Engineering, SCSE 2022

Conference

Conference2022 International Research Conference on Smart Computing and Systems Engineering, SCSE 2022
Country/TerritorySri Lanka
CityColombo
Period1/09/22 → …

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