A novel transformer using dynamic range-enhanced discrete cosine transform for detecting bean leaf diseases.

ABSTRACT:

Introduction

Early detection of diseases on bean leaves is essential for preventing declines in agricultural productivity and mitigating broader agricultural challenges. However, some bean leaf diseases are difficult to detect even with the human eye, posing significant challenges for machine learning methods that rely on precise feature extraction.

Methods

We propose a novel approach, DCT-Transformers, which combines a preprocessing technique, dynamic range enhanced discrete cosine transform (DRE-DCT) with Transformer-based models. The DRE-DCT method enhances the dynamic range of input images by extracting high-frequency components and subtle details that are typically imperceptible while preserving overall image quality. Transformer models were then used to classify bean l

SUBMITTER: Ince IF 

PROVIDER: S-EPMC12426951 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature