Recognition of Greenhouse Cucumber Disease Based on Image Processing Technology

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Open Journal of Applied Sciences

ISSN Print: 2165-3917
ISSN Online: 2165-3925
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"Recognition of Greenhouse Cucumber Disease Based on Image Processing Technology"
written by Dong Pixia, Wang Xiangdong,
published by Open Journal of Applied Sciences, Vol.3 No.1B, 2013

has been cited by the following article(s):

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[64]	Cucumber disease recognition based on Global-Local Singular value decomposition
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[65]	Automated detection of Mycosphaerella melonis infected cucumber fruits
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[13]	A new approach to detect mildew disease on cucumber (Pseudoperonospora cubensis) leaves with image processing Journal of Plant Pathology, 2022 DOI:10.1007/s42161-022-01178-z

[14]	An Experimental Evaluation in Plant Disease Identification Based on Activation-Reconstruction Generative Adversarial Network 2022 2nd International Conference on Advance Computing and Innovative Technologies in Engineering (ICACITE), 2022 DOI:10.1109/ICACITE53722.2022.9823924

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[16]	A new approach to detect mildew disease on cucumber (Pseudoperonospora cubensis) leaves with image processing Journal of Plant Pathology, 2022 DOI:10.1007/s42161-022-01178-z

[17]	A Systematic Literature Survey on Generative Adversarial Network Based Crop Disease Identification 2021 International Conference on Technological Advancements and Innovations (ICTAI), 2021 DOI:10.1109/ICTAI53825.2021.9673159

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[24]	Machine Vision-based Expert System for Automated Cucumber Diseases Recognition and Classification 2021 International Conference on INnovations in Intelligent SysTems and Applications (INISTA), 2021 DOI:10.1109/INISTA52262.2021.9548607

[25]	Rice diseases detection using Convolutional Neural Networks: A Survey 2021 International Conference on Advance Computing and Innovative Technologies in Engineering (ICACITE), 2021 DOI:10.1109/ICACITE51222.2021.9404620

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[27]	An automated system for cucumber leaf diseased spot detection and classification using improved saliency method and deep features selection Multimedia Tools and Applications, 2020 DOI:10.1007/s11042-020-08726-8

[28]	A Comprehensive Survey on Pest Detection Techniques using Image Processing 2020 4th International Conference on Intelligent Computing and Control Systems (ICICCS), 2020 DOI:10.1109/ICICCS48265.2020.9120889

[29]	Graph Constraint and Collaborative Representation Classifier Steered Discriminative Projection with Applications for the Early Identification of Cucumber Diseases Sensors, 2020 DOI:10.3390/s20041217

[30]	Machine Learning for Plant Leaf Disease Detection and Classification – A Review 2019 International Conference on Communication and Signal Processing (ICCSP), 2019 DOI:10.1109/ICCSP.2019.8698004

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[33]	Crop Organ Segmentation and Disease Identification Based on Weakly Supervised Deep Neural Network Agronomy, 2019 DOI:10.3390/agronomy9110737

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[35]	AI-Powered Image-Based Tomato Leaf Disease Detection 2019 Third International conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC), 2019 DOI:10.1109/I-SMAC47947.2019.9032621

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[41]	Unsupervised Segmentation of Greenhouse Plant Images Based on Statistical Method Scientific Reports, 2018 DOI:10.1038/s41598-018-22568-3

[42]	Unsupervised Segmentation of Greenhouse Plant Images Based on Statistical Method Scientific Reports, 2018 DOI:10.1038/s41598-018-22568-3

[43]	Leaf image based cucumber disease recognition using sparse representation classification Computers and Electronics in Agriculture, 2017 DOI:10.1016/j.compag.2017.01.014

[44]	Detection of Silybum marianum infection with Microbotryum silybum using VNIR field spectroscopy Computers and Electronics in Agriculture, 2017 DOI:10.1016/j.compag.2017.03.017

[45]	Fusion of superpixel, expectation maximization and PHOG for recognizing cucumber diseases Computers and Electronics in Agriculture, 2017 DOI:10.1016/j.compag.2017.06.016

[46]	Study of digital image processing techniques for leaf disease detection and classification Multimedia Tools and Applications, 2017 DOI:10.1007/s11042-017-5445-8

[47]	The Disease Assessment of Cucumber Downy Mildew Based on Image Processing 2017 International Conference on Computer Network, Electronic and Automation (ICCNEA), 2017 DOI:10.1109/ICCNEA.2017.65

[48]	Real time automatic bruise detection in (Apple) fruits using thermal camera 2017 International Conference on Communication and Signal Processing (ICCSP), 2017 DOI:10.1109/ICCSP.2017.8286542

[49]	An individual grape leaf disease identification using leaf skeletons and KNN classification 2017 International Conference on Innovations in Information, Embedded and Communication Systems (ICIIECS), 2017 DOI:10.1109/ICIIECS.2017.8275951

[50]	Detection of Powdery Mildew Disease of Beans in India : A Review Oriental journal of computer science and technology, 2016 DOI:10.13005/ojcst/09.03.08

[51]	Cucumber disease recognition based on Global-Local Singular value decomposition Neurocomputing, 2016 DOI:10.1016/j.neucom.2016.04.034

[52]	Automated Detection of Mycosphaerella Melonis Infected Cucumber Fruits IFAC-PapersOnLine, 2016 DOI:10.1016/j.ifacol.2016.10.020

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