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Published in:
2023 | OriginalPaper | Chapter
Identification and Detection of Plant Disease Using Transfer Learning
Authors : Neelam Sunil Khasgiwala, R. R. Sedamkar
Published in: Intelligent Computing and Networking
Publisher: Springer Nature Singapore
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Abstract
Many researchers have recently been inspired by the success of deep learning algorithms in the field of artificial intelligence to improve plant disease detection performance. Deep learning's main goal is to teach computers how to solve real-world problems using data or experience. Detecting diseases is a critical task for farmers. They take shortcuts such as using chemical pesticides, which have negative effects on consumable foods. So, in this paper, we used deep learning algorithms to detect plant diseases. Deep learning is a popular trend in which technological benefits can be imparted to the agricultural field. Detecting plant diseases with deep learning techniques is less expensive than using chemical pesticides. This paper reviews existing techniques and recommends the best technique that farmers can use to identify disease faster and at a lower cost.