<p class="jove_content">The proposed method aims to accurately diagnose and classify tomato plant diseases using image enhancement, SIFT-based feature extraction, COA-driven feature selection, and a cross-attention aided convolutional stacking sparse autoencoder.</p>

a-transform-based-extraction-advanced-cross-attention-aided

A Transform-Based Extraction and Advanced Cross-Attention-Aided Convolutional Stacked Sparse Autoencoder for Tomato Disease Detection

Low agricultural productivity is significantly influenced by plant diseases. Most farmers find it difficult to accurately recognize and effectively ...

Institution - Excel Engineering College (Autonomous)

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