Abstract
In our first paper, we talked about the problems farmers face, and we introduced LeafAI, Plant disease detection app, as a way to help.Now, in this new paper, we're explaining how we actually made LeafAI work in the real world.Deep learning is a branch of artificial intelligence.In recent years, deep learning has brought tremendous improvements in the recognition accuracy of image classification and object detection systems.Hence, in this paper, we utilized convolutional neural network (CNN)-based pre-trained models for efficient plant disease identification.An Android application that utilizes deep learning techniques to detect and diagnose plant diseases from images of plant leaves.The application should empower users, including farmers and gardeners, to quickly identify and take action against plant diseases, there by improving crop health and yield.
Abstract from the paper’s OpenAlex record; open copy licensed other-oa. Read at the source ↗
The text the model read, with the source record’s inline markup (italics, sub- and superscripts) rendered and its character entities decoded; quote offsets refer to the raw text.
Claims 1
Claim · model-written summary
The authors developed a CNN-based Android application for plant disease identification from leaf images.
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Verbatim
e0“An Android application that utilizes deep learning techniques to detect and diagnose plant diseases from images of plant leaves.”