A Review of Leaf Diseases Detection and Classification by Deep Learning

Creative Commons License

Doutoum A. S., Tuğrul B.

IEEE ACCESS, cilt.11, sa.11, ss.119219-119230, 2023 (SCI-Expanded)

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 11 Sayı: 11
  • Basım Tarihi: 2023
  • Doi Numarası: 10.1109/access.2023.3326721
  • Dergi Adı: IEEE ACCESS
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Compendex, INSPEC, Directory of Open Access Journals
  • Sayfa Sayıları: ss.119219-119230
  • Ankara Üniversitesi Adresli: Evet

Özet

Leaf’s primary function is to produce nutrients through photosynthesis and support the plant’s growth. Leaf diseases caused by bacteria or other pathogens can negatively impact agricultural yields. Immediate and early diagnosis of diseases is vital for plant health. The significant development of deep learning algorithms for leaf disease classification and detection contributed to a solid tool with a robust and reliable accuracy rate. This study presents a comprehensive review of leaf disease research in the literature. It also highlights the gaps that need to be filled as well as the obstacles and problems facing research projects. The total number of papers retrieved from five electronic databases is 256. We analyzed and classified them into seven research questions. The results demonstrate that 63% of the papers are journal articles, 35% are conference papers, and 2% are workshop papers.