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A crucial component of precision agriculture is leaf disease identification, which allows for early intervention to stop crop losses and guarantee food security. Hyperspectral imaging has become effective since it records data over a broad range of wavelengths. When paired with deep learning techniques, hyperspectral images can identify and classify different leaf diseases reliably. This study examines current developments in leaf disease detection using hyperspectral imaging and deep learning. We discuss the fundamental ideas of hyperspectral imaging, the different kinds of deep learning algorithms used, and the difficulties and potential paths ahead in this area.

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Leaf Disease Classification with Deep Learning: A Hyperspectral Imaging Perspective

  • 会议论文

  • 发表日期：

    2025年

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  • Bhavika N. Patel,
  • Jitendra P. Chaudhari

摘要

A crucial component of precision agriculture is leaf disease identification, which allows for early intervention to stop crop losses and guarantee food security. Hyperspectral imaging has become effective since it records data over a broad range of wavelengths. When paired with deep learning techniques, hyperspectral images can identify and classify different leaf diseases reliably. This study examines current developments in leaf disease detection using hyperspectral imaging and deep learning. We discuss the fundamental ideas of hyperspectral imaging, the different kinds of deep learning algorithms used, and the difficulties and potential paths ahead in this area.