Plant Disease Detection using Deep Learning

Author:

Abstract

[Context] Plants play an essential role in climate change, agriculture industry and a country’s economy. Thereby taking care of plants is very crucial. Just like humans, plants are effected by several disease caused by bacteria, fungi and virus. Identification of these disease timely and curing them is essential to prevent whole plant from destruction. [Objective] This paper proposes a deep learning based model named plant disease detector. The model is able to detect several diseases from plants using pictures of their leaves. [Methodology] Plant disease detection model is developed using neural network. First of all augmentation is applied on dataset to increase the sample size. Later Convolution Neural Network (CNN) is used with multiple convolution and pooling layers. PlantVillage dataset is used to train the model. After training the model, it is tested properly to validate the results. [Results] We have performed different experiments using this model. 15% of data from PlantVillage data is used for testing purpose that contains images of healthy as well as diseased plants. Proposed model has achieved 98.3% testing accuracy. [Conclusion] This study is focused on deep learning model to detect disease in plant leave. But, in future model can be integrated with drone or any other system to live detect diseases from plants and report the diseased plants location to people so that they can be cured accordingly.

Publisher

Blue Eyes Intelligence Engineering and Sciences Engineering and Sciences Publication - BEIESP

Subject

Management of Technology and Innovation,General Engineering

Cited by 52 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Enhanced deep learning model architecture for plant disease detection in Chilli plants;Journal of Edge Computing;2024-07-20

2. LLaVA-PlantDiag: Integrating Large-scale Vision-Language Abilities for Conversational Plant Pathology Diagnosis;2024 International Joint Conference on Neural Networks (IJCNN);2024-06-30

3. Borage Leaf Disease Detection using Deep Learning Models;2024 3rd International Conference on Applied Artificial Intelligence and Computing (ICAAIC);2024-06-05

4. Plant Disease Detection and Diagnosis;2024 5th International Conference for Emerging Technology (INCET);2024-05-24

5. Machine and Deep Learning Approaches for Crop Disease Detection: An In-Depth Analysis;2024 IEEE 9th International Conference for Convergence in Technology (I2CT);2024-04-05

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