Pomegranate Leaf Disease Classification using Feature Extraction and Machine Learning

Nirmal, M.D.; Jadhav, Pramod; Pawar, Santosh

doi:10.1109/icosec54921.2022.9951907

Cited by 5 publications

(2 citation statements)

References 11 publications

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“…Year Learning Type Technique Performance Accuracy (%) [15] 2020 Machine Learning GMM+ROI 85 [36] 2022 Machine Learning LDA+NB 96 [37] 2022 Machine Learning SVM 96 [38] 2023 Machine Learning GLCM+SVM 83 Our 2024 Transfer Learning Novel CRnet 98…”

Section: Refmentioning

confidence: 99%

A Novel Transfer Learning Approach for Detection of Pomegranates Growth Stages

Naseer,

Amjad,

Raza

et al. 2024

IEEE Access

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Section: Refmentioning

confidence: 99%

A Novel Transfer Learning Approach for Detection of Pomegranates Growth Stages

Naseer,

Amjad,

Raza

et al. 2024

IEEE Access

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“…Users are able to transfer their data and applications to the cloud using the CC [3]. Large numbers of customers that use CC are drawn to cloud service providers (CSPs) because of the unique services, flexible usage, and cost reductions that they give [4]. On the other hand, cloud data migration might be challenging due to operational and security concerns [5].…”

Section: Introductionmentioning

confidence: 99%

Cloud Data Transfer and Harmful Activity Detection using

Venkatesan¹,

Jothiprakash²,

Nalini³

2023

IJSMEM

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Many sectors have begun adopting cloud computing. The hazards associated with virtualization and the dispersed nature of the cloud have resulted in a number of reported security threats and attacks. The complicated system and robust design necessitate a foundation of the fundamentals. In this paper, we introduce a fool proof system for authenticating and exchanging cloud data. An effective IPSO-KELM can identify malicious actions taken by users. The origin of the data is verified first. The IPSO-KELM then decides whether the data was malicious or authentic once the sender has been verified and before it is sent to the cloud. The SHA256-RSA technique protects normal data in transit. In this article, we compare and contrast the suggested IPSO-KELM and SHA256-RSA technique to identifying fraudulent users and sharing data in the cloud with other methods.

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A Systematic Review of Pomegranate Fruit Disease Detection and Classification Using Machine Learning and Deep Learning Techniques

Pakruddin,

Hemavathy

2024

Lecture Notes in Networks and Systems

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Pomegranate Leaf Disease Classification using Feature Extraction and Machine Learning

Cited by 5 publications

References 11 publications

A Novel Transfer Learning Approach for Detection of Pomegranates Growth Stages

A Novel Transfer Learning Approach for Detection of Pomegranates Growth Stages

Cloud Data Transfer and Harmful Activity Detection using

A Systematic Review of Pomegranate Fruit Disease Detection and Classification Using Machine Learning and Deep Learning Techniques

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