Title: Seeker optimisation algorithm with deep learning based feature fusion model for tomato plant leaf disease detection

Authors: K. Jayaprakash; S.P. Balamurugan

Addresses: Department of Computer and Information Science, Annamalai University, Chidambaram, Tamil Nadu, 608002, India ' Department of Computer and Information Science, Annamalai University, Chidambaram, Tamil Nadu, 608002, India

Abstract: The study focus on design and development of the seeker optimisation algorithm with deep learning based feature fusion model for tomato plant leaf disease detection (SOADLF-TPLDD) technique. The goal of the SOADLF-TPLDD technique is to apply DL technique for the segmentation and classification of plant disease. In the primary stage, the SOADLF-TPLDD technique uses U2Net model for background removal and UNet PP model for segmentation process. Besides, a feature fusion of two DL models takes place namely InceptionV3+EfficientNetB2. For disease detection and classification, Attention Convolutional Gated Recurrent Unit (ACGRU) model is applied. Furthermore, the SOA is used for optimal hyperparameter selection of the ACGRU model. Finally, the recommendation of pesticides for the detected plant diseases takes place using matrix factorisation (MF) approach. The stimulation outcomes of the SOADLF-TPLDD method on benchmark dataset are validated and the outcomes represented the betterment of the SOADLF-TPLDD method over other existing techniques.

Keywords: tomato; plant leaf diseases; deep learning; segmentation; seeker optimisation algorithm.

DOI: 10.1504/IJSSE.2025.151323

International Journal of System of Systems Engineering, 2025 Vol.15 No.6, pp.580 - 596

Received: 16 Aug 2023
Accepted: 26 Sep 2023
Published online: 23 Jan 2026 *

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