# Identify Apple Leaf Diseases Using Deep Learning Algorithm

Source: [Identify Apple Leaf Diseases Using Deep Learning Algorithm](<https://www.sota2.com/research/paper/68fa6a781e209131cea285be>)

Collection index: [llms.txt](<https://www.sota2.com/research/llms.txt>)

Data updated: 2025-10-25T23:25:36.663Z

Authors: Daping Zhang, Hongyu Yang, Jiayu Cao

Published: 2021-07-27T04:55:16.000Z

## Abstract

Agriculture is an essential industry in the both society and economy of a country. However, the pests and diseases cause a great amount of reduction in agricultural production while there is not sufficient guidance for farmers to avoid this disaster. To address this problem, we apply CNNs to plant disease recognition by building a classification model. Within the dataset of 3,642 images of apple leaves, We use a pre-trained image classification model Restnet34 based on a Convolutional neural network (CNN) with the Fastai framework in order to save the training time. Overall, the accuracy of classification is 93.765%.

## Recorded benchmark results

A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage.

## Original sources and implementation

[Original paper](<https://arxiv.org/abs/2107.12598>)

[PDF](<https://arxiv.org/pdf/2107.12598.pdf>)