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A bean plant is rich in protein, carbs, zinc, and iron. Numerous bean varieties, including kidney beans, are high in antinutrients, which prevent the body’s enzymes from performing some functions. Beans that are high in phytates and phytic acid prevent the metabolism of vitamin D and hinder bone formation. But some maladies such as angular leaf spot, bean rust, halo blight, white mold, bacterial wilt, etc., along with some pests, namely aphids, armyworms, etc., have a repercussion on its production. The intent of this work is to compare the results of customized CNN on augmented and original data with transfer learning methods, such as VGG-16, ResNet50, and EfficientNet, that can identify plant diseases at an early stage. The beans dataset available on Tensor Flow is used for the experiment. In comparison, the highest accuracy of 98.75% was given by ResNet50 model.

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Disease Detection in Beans Leaves Using Transfer Learning

  • 会议论文

  • 发表日期：

    2025年

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  • Riya Rawal,
  • Anuradha Chug,
  • Amit P. Singh

摘要

A bean plant is rich in protein, carbs, zinc, and iron. Numerous bean varieties, including kidney beans, are high in antinutrients, which prevent the body’s enzymes from performing some functions. Beans that are high in phytates and phytic acid prevent the metabolism of vitamin D and hinder bone formation. But some maladies such as angular leaf spot, bean rust, halo blight, white mold, bacterial wilt, etc., along with some pests, namely aphids, armyworms, etc., have a repercussion on its production. The intent of this work is to compare the results of customized CNN on augmented and original data with transfer learning methods, such as VGG-16, ResNet50, and EfficientNet, that can identify plant diseases at an early stage. The beans dataset available on Tensor Flow is used for the experiment. In comparison, the highest accuracy of 98.75% was given by ResNet50 model.