Digital image processing techniques for detecting, quantifying and classifying plant diseases

JG Arnal Barbedo - SpringerPlus, 2013 - Springer
This paper presents a survey on methods that use digital image processing techniques to
detect, quantify and classify plant diseases from digital images in the visible spectrum …

Non-destructive techniques of detecting plant diseases: A review

MM Ali, NA Bachik, NA Muhadi, TNT Yusof… - … and Molecular Plant …, 2019 - Elsevier
Plant diseases contribute to significant economic and post-harvest losses in agricultural
production sector all over the world. Early detection of plant diseases and pathogens is …

Image recognition of four rice leaf diseases based on deep learning and support vector machine

F Jiang, Y Lu, Y Chen, D Cai, G Li - Computers and Electronics in …, 2020 - Elsevier
In the field of agricultural information, identification and prediction of rice leaf diseases has
always been a research focus. Deep learning and support vector machine (SVM) technology …

[HTML][HTML] Performance analysis of deep learning CNN models for disease detection in plants using image segmentation

P Sharma, YPS Berwal, W Ghai - Information Processing in Agriculture, 2020 - Elsevier
Food security for the 7 billion people on earth requires minimizing crop damage by timely
detection of diseases. Most deep learning models for automated detection of diseases in …

A novel approach for rice plant diseases classification with deep convolutional neural network

SK Upadhyay, A Kumar - International Journal of Information Technology, 2022 - Springer
Agriculture is one of the major revenue-producing fields and a source of livelihood in India.
On the largest regions in India, rice is cultivated as an essential food. It is observed that rice …

Detection and classification of citrus diseases in agriculture based on optimized weighted segmentation and feature selection

M Sharif, MA Khan, Z Iqbal, MF Azam, MIU Lali… - … and electronics in …, 2018 - Elsevier
In agriculture, plant diseases are primarily responsible for the reduction in production which
causes economic losses. In plants, citrus is used as a major source of nutrients like vitamin …

Crop conditional Convolutional Neural Networks for massive multi-crop plant disease classification over cell phone acquired images taken on real field conditions

A Picon, M Seitz, A Alvarez-Gila, P Mohnke… - … and Electronics in …, 2019 - Elsevier
Abstract Convolutional Neural Networks (CNN) have demonstrated their capabilities on the
agronomical field, especially for plant visual symptoms assessment. As these models grow …

A review of advanced machine learning methods for the detection of biotic stress in precision crop protection

J Behmann, AK Mahlein, T Rumpf, C Römer… - Precision …, 2015 - Springer
Effective crop protection requires early and accurate detection of biotic stress. In recent
years, remarkable results have been achieved in the early detection of weeds, plant …

Development of soft computing and applications in agricultural and biological engineering

Y Huang, Y Lan, SJ Thomson, A Fang… - … and electronics in …, 2010 - Elsevier
Soft computing is a set of “inexact” computing techniques, which are able to model and
analyze very complex problems. For these complex problems, more conventional methods …

[PDF][PDF] Soybean plant disease identification using convolutional neural network

S Wallelign, M Polceanu, C Buche - The thirty-first international flairs …, 2018 - cdn.aaai.org
Plants have become an important source of energy, and are a fundamental piece in the
puzzle to solve the problem of global warming. However, plant diseases are threatening the …