Proceedings ArticleDOI
Plant Disease Detection Using CNN
TLDR
A CNN based method for plant disease detection has been proposed here and performs well in terms of time complexity and the area of the infected region.Abstract:
Agricultural productivity is a key component of Indian economy. Therefore the contribution of food crops and cash crops is highly important for both the environment and human beings. Every year crops succumb to several diseases. Due to inadequate diagnosis of such diseases and not knowing symptoms of the disease and its treatment many plants die. This study provides insights into an overview of the plant disease detection using different algorithms. A CNN based method for plant disease detection has been proposed here. Simulation study and analysis is done on sample images in terms of time complexity and the area of the infected region. It is done by image processing technique. A total of 15 cases have been fed to the model, out of which 12 cases are of diseased plant leaves namely, Bell Paper Bacterial Spot, Potato Early Blight, Potato Late Blight, Tomato Target Spot, Tomato Mosaic Virus, Tomato Yellow Leaf Curl Virus, Tomato Bacterial Spot, Tomato Early Blight, Tomato Late Blight, Tomato Leaf Mold, Tomato Septoria Leaf Spot and Tomato Spider Mites and 3 cases of healthy leaves namely, Bell Paper Healthy, Potato Healthy and Tomato Healthy. Test accuracy is obtained as 88.80%. Different performance matrices are derived for the same.read more
Citations
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Journal ArticleDOI
Transfer learning-based deep ensemble neural network for plant leaf disease detection
TL;DR: Performance evaluation of the proposed DENN technique demonstrates that effective in categorizing various types of plant diseases that comparatively outperform pre-trained models.
Journal ArticleDOI
Comparison of Artificial Intelligence Algorithms in Plant Disease Prediction
TL;DR: This paper uses Mасhine Learning (ML) and Deep Learning (DL) algorithms to detect, classify and рrediсt the роssible раthоgens/diseases in the ураrtiсulаr type оf сrор/рlаnt сosnsidering based on weather соnditiоns.
Proceedings ArticleDOI
Review on Leaf diseases detection using Deep learning
Shweta Bondre,Ashish Sharma +1 more
TL;DR: Deep learning is the golden age of machine learning (ML) and it is now helping to identify and classify plant diseases early as discussed by the authors, which is very normal and natural which decreases the crop productivity.
Proceedings ArticleDOI
Plant Disease Identification Using Deep Learning: A Systematic Review
TL;DR: In this article, the authors present a review to examine the power of these techniques in detection for plant diseases and add in the agriculture advancement, which enfolds larger scope of deep learning in the future research while detecting plant diseases along with improvised performance and accuracy.
Proceedings ArticleDOI
Plant Disease Identification from Leaf Images using Deep CNN’s EfficientNet
Akibur Rahman Prodeep,A. S. M. Morshedul Hoque,Md. Mohsin Kabir,Md. Saifur Rahman,Mohammed Firoz Mridha +4 more
TL;DR: The exploratory outcomes approve that the EfficientNet performs better in multilabel plant illness classification tasks and track down that a CNN architecture, skip associations, spatial convolutions, and more limited secret layer network impact better outcomes in plant illness characterization.
References
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Journal ArticleDOI
Fast and Accurate Detection and Classification of Plant Diseases
TL;DR: The experimental results demonstrate that the proposed technique is a robust technique for the detection of plant leaves diseases and can achieve 20% speedup over the approach proposed in [1].
Proceedings ArticleDOI
Plant Leaf Disease Detection and Classification Based on CNN with LVQ Algorithm
TL;DR: A Convolutional Neural Network model and Learning Vector Quantization algorithm based method for tomato leaf disease detection and classification and results validate that the proposed method effectively recognizes four different types of tomato leaf diseases.
Proceedings ArticleDOI
Detection of potato diseases using image segmentation and multiclass support vector machine
TL;DR: The proposed approach presents a path toward automated plant diseases diagnosis on a massive scale and integrates image processing and machine learning to allow diagnosing diseases from leaf images.
Proceedings ArticleDOI
Image processing for smart farming: Detection of disease and fruit grading
TL;DR: Effective algorithms for spread of disease and mango counting are demonstrated and artificial neural network concept is used for practical implementation using MATLAB.
Journal ArticleDOI
New Optimized Spectral Indices for Identifying and Monitoring Winter Wheat Diseases
Wenjiang Huang,Qingsong Guan,Juhua Luo,Jingcheng Zhang,Jinling Zhao,Dong Liang,Linsheng Huang,Dongyan Zhang +7 more
TL;DR: The detection of the severity of yellow rust using the yellow rust-index (YRI) showed a high coefficient of determination between the estimated DI and its observations, suggesting that the NSIs may improve disease detection in precision agriculture application.
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