Modification of Sand Cat Swarm Optimization for Classification Problems

The proposed system represents an enhanced version in search of food of Sand Cat based on Levy distribution and Firework algorithm for the image classification of grape leaf diseases. In the preprocessing step, the proposed system utilizes convolution kernels to transform images into input data within the range of (0,1). Successively, the Levy distribution and Firework algorithm are incorporated into the SCSO model as an exploration search mechanism. The study employed a grape leaf dataset sourced from the Plant Village project (www.plantvillage.org), comprising 4062 labeled images measuring 256 by 256 pixels and categorized into 4 distinct classes: healthy, Black Rot, Black Measles, and Isariopsis leaf spot, which was utilized to evaluate the efficacy of the proposed system. The experimental findings demonstrate that the proposed system outperforms the analyses of VGG16, GLCM with SVM, Low contrast haze reduction-neighborhood component analysis with SVM, and SCSO.

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Published
2024-08-23
DOI
https://doi.org/10.1109/ibdap62940.2024.10689683
Citations
1
Primary Topic
Metaheuristic Optimization Algorithms Research
Type
article
Field-Weighted Citation Impact
0.35

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article

Modification of Sand Cat Swarm Optimization for Classification Problems

Sakkayaphop Pravesjit, Sathien Hunta, Arit Thammano, Duangjai Jitkongchuen et al.
1 citations
Metaheuristic Optimization Algorithms Research
0.35
article

Modification of Sand Cat Swarm Optimization for Classification Problems

Sakkayaphop Pravesjit, Sathien Hunta, Arit Thammano, Duangjai Jitkongchuen, Krittika Kantawong, Panchit Longpradit
article en
1 citations

Abstract

The proposed system represents an enhanced version in search of food of Sand Cat based on Levy distribution and Firework algorithm for the image classification of grape leaf diseases. In the preprocessing step, the proposed system utilizes convolution kernels to transform images into input data within the range of (0,1). Successively, the Levy distribution and Firework algorithm are incorporated into the SCSO model as an exploration search mechanism. The study employed a grape leaf dataset sourced from the Plant Village project (www.plantvillage.org), comprising 4062 labeled images measuring 256 by 256 pixels and categorized into 4 distinct classes: healthy, Black Rot, Black Measles, and Isariopsis leaf spot, which was utilized to evaluate the efficacy of the proposed system. The experimental findings demonstrate that the proposed system outperforms the analyses of VGG16, GLCM with SVM, Low contrast haze reduction-neighborhood component analysis with SVM, and SCSO.

Vol. 53
Mahidol University (TH), University of Phayao (TH), King Mongkut's Institute of Technology Ladkrabang (TH)
University of Phayao
Openalex Percentile: Top 33%
Metaheuristic Optimization Algorithms Research
0.35
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Modification of Sand Cat Swarm Optimization for Classification Problems — Sakkayaphop Pravesjit, Sathien Hunta, et al. · (2024) | TGRS Research Map | TGRS