Plant diseases recognition on images using convolutional neural networks: A systematic review
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Title
Plant diseases recognition on images using convolutional neural networks: A systematic review
Authors
Keywords
Plant diseases, Convolutional neural networks, Crop disease recognition, Plant pathogen, SLR
Journal
COMPUTERS AND ELECTRONICS IN AGRICULTURE
Volume 185, Issue -, Pages 106125
Publisher
Elsevier BV
Online
2021-05-01
DOI
10.1016/j.compag.2021.106125
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Note: Only part of the references are listed.- Deep Learning: Current State
- (2020) Joaquin Salas et al. IEEE Latin America Transactions
- A State-of-the-Art Survey on Deep Learning Theory and Architectures
- (2019) Md Zahangir Alom et al. Electronics
- A Mobile-Based Deep Learning Model for Cassava Disease Diagnosis
- (2019) Amanda Ramcharan et al. Frontiers in Plant Science
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- (2019) Gerrit Polder et al. Frontiers in Plant Science
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- (2019) Wan-jie Liang et al. Scientific Reports
- Correction to: Detection and analysis of wheat spikes using Convolutional Neural Networks
- (2019) Md Mehedi Hasan et al. Plant Methods
- Recognition Pest by Image-Based Transfer Learning
- (2019) Wang Dawei et al. JOURNAL OF THE SCIENCE OF FOOD AND AGRICULTURE
- Analysis of transfer learning for deep neural network based plant classification models
- (2019) Aydin Kaya et al. COMPUTERS AND ELECTRONICS IN AGRICULTURE
- PD2SE-Net: Computer-assisted plant disease diagnosis and severity estimation network
- (2019) Qiaokang Liang et al. COMPUTERS AND ELECTRONICS IN AGRICULTURE
- Plant disease identification from individual lesions and spots using deep learning
- (2019) Jayme Garcia Arnal Barbedo BIOSYSTEMS ENGINEERING
- Detection of Apple Lesions in Orchards Based on Deep Learning Methods of CycleGAN and YOLOV3-Dense
- (2019) Yunong Tian et al. Journal of Sensors
- Identification of plant leaf diseases using a nine-layer deep convolutional neural network
- (2019) Geetharamani G. et al. COMPUTERS & ELECTRICAL ENGINEERING
- Cucumber leaf disease identification with global pooling dilated convolutional neural network
- (2019) Shanwen Zhang et al. COMPUTERS AND ELECTRONICS IN AGRICULTURE
- Deep neural networks with transfer learning in millet crop images
- (2019) Solemane Coulibaly et al. COMPUTERS IN INDUSTRY
- Citrus Pests and Diseases Recognition Model Using Weakly Dense Connected Convolution Network
- (2019) Shuli Xing et al. SENSORS
- AI-powered banana diseases and pest detection
- (2019) Michael Gomez Selvaraj et al. Plant Methods
- Plant disease identification using explainable 3D deep learning on hyperspectral images
- (2019) Koushik Nagasubramanian et al. Plant Methods
- Classification of Plant Leaf Diseases Based on Improved Convolutional Neural Network
- (2019) Hang et al. SENSORS
- Depthwise separable convolution architectures for plant disease classification
- (2019) Kamal KC et al. COMPUTERS AND ELECTRONICS IN AGRICULTURE
- Novel data augmentation strategies to boost supervised segmentation of plant disease
- (2019) Clément Douarre et al. COMPUTERS AND ELECTRONICS IN AGRICULTURE
- Automatic detection and classification of leaf spot disease in sugar beet using deep learning algorithms
- (2019) Mehmet Metin Ozguven et al. PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
- Millimeter-Level Plant Disease Detection From Aerial Photographs via Deep Learning and Crowdsourced Data
- (2019) Tyr Wiesner-Hanks et al. Frontiers in Plant Science
- Identification of Tomato Disease Types and Detection of Infected Areas Based on Deep Convolutional Neural Networks and Object Detection Techniques
- (2019) Qimei Wang et al. Computational Intelligence and Neuroscience
- Factors influencing the use of deep learning for plant disease recognition
- (2018) Jayme G.A. Barbedo BIOSYSTEMS ENGINEERING
- Three-channel convolutional neural networks for vegetable leaf disease recognition
- (2018) Shanwen Zhang et al. Cognitive Systems Research
- Classification of apple leaf conditions in hyper-spectral images for diagnosis of Marssonina blotch using mRMR and deep neural network
- (2018) Keunho Park et al. COMPUTERS AND ELECTRONICS IN AGRICULTURE
- Deep convolutional neural networks for mobile capture device-based crop disease classification in the wild
- (2018) Artzai Picon et al. COMPUTERS AND ELECTRONICS IN AGRICULTURE
- Deep learning models for plant disease detection and diagnosis
- (2018) Konstantinos P. Ferentinos COMPUTERS AND ELECTRONICS IN AGRICULTURE
- A comparative study of fine-tuning deep learning models for plant disease identification
- (2018) Edna Chebet Too et al. COMPUTERS AND ELECTRONICS IN AGRICULTURE
- DeepLab: Semantic Image Segmentation with Deep Convolutional Nets, Atrous Convolution, and Fully Connected CRFs
- (2018) Liang-Chieh Chen et al. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
- An explainable deep machine vision framework for plant stress phenotyping
- (2018) Sambuddha Ghosal et al. PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
- Deep Learning: Individual Maize Segmentation From Terrestrial Lidar Data Using Faster R-CNN and Regional Growth Algorithms
- (2018) Shichao Jin et al. Frontiers in Plant Science
- Identification of Maize Leaf Diseases Using Improved Deep Convolutional Neural Networks
- (2018) Xihai Zhang et al. IEEE Access
- UAV based wilt detection system via convolutional neural networks
- (2018) L. Minh Dang et al. Sustainable Computing-Informatics & Systems
- A recognition method for cucumber diseases using leaf symptom images based on deep convolutional neural network
- (2018) Juncheng Ma et al. COMPUTERS AND ELECTRONICS IN AGRICULTURE
- Impact of dataset size and variety on the effectiveness of deep learning and transfer learning for plant disease classification
- (2018) Jayme Garcia Arnal Barbedo COMPUTERS AND ELECTRONICS IN AGRICULTURE
- High-Performance Deep Neural Network-Based Tomato Plant Diseases and Pests Diagnosis System With Refinement Filter Bank
- (2018) Alvaro F. Fuentes et al. Frontiers in Plant Science
- CCDF: Automatic system for segmentation and recognition of fruit crops diseases based on correlation coefficient and deep CNN features
- (2018) Muhammad Attique Khan et al. COMPUTERS AND ELECTRONICS IN AGRICULTURE
- Deep leaning approach with colorimetric spaces and vegetation indices for vine diseases detection in UAV images
- (2018) Mohamed Kerkech et al. COMPUTERS AND ELECTRONICS IN AGRICULTURE
- Using Deep Learning for Image-Based Potato Tuber Disease Detection
- (2018) Dor Oppenheim et al. PHYTOPATHOLOGY
- Comparison of SIFT Encoded and Deep Learning Features for the Classification and Detection of Esca Disease in Bordeaux Vineyards
- (2018) Florian Rançon et al. Remote Sensing
- An effective algorithm for hyperparameter optimization of neural networks
- (2017) G. I. Diaz et al. IBM JOURNAL OF RESEARCH AND DEVELOPMENT
- SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation
- (2017) Vijay Badrinarayanan et al. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
- Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks
- (2017) Shaoqing Ren et al. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
- Deep convolutional neural network for classifying Fusarium wilt of radish from unmanned aerial vehicles
- (2017) Jin Gwan Ha et al. Journal of Applied Remote Sensing
- Identification of rice diseases using deep convolutional neural networks
- (2017) Yang Lu et al. NEUROCOMPUTING
- Automated Identification of Northern Leaf Blight-Infected Maize Plants from Field Imagery Using Deep Learning
- (2017) Chad DeChant et al. PHYTOPATHOLOGY
- Fine-grained recognition of plants from images
- (2017) Milan Šulc et al. Plant Methods
- Super-Resolution of Plant Disease Images for the Acceleration of Image-based Phenotyping and Vigor Diagnosis in Agriculture
- (2017) Kyosuke Yamamoto et al. SENSORS
- A Robust Deep-Learning-Based Detector for Real-Time Tomato Plant Diseases and Pests Recognition
- (2017) Alvaro Fuentes et al. SENSORS
- Deep Learning for Image-Based Cassava Disease Detection
- (2017) Amanda Ramcharan et al. Frontiers in Plant Science
- Identification of Apple Leaf Diseases Based on Deep Convolutional Neural Networks
- (2017) Bin Liu et al. Symmetry-Basel
- A review on the main challenges in automatic plant disease identification based on visible range images
- (2016) Jayme Garcia Arnal Barbedo BIOSYSTEMS ENGINEERING
- Food system consequences of a fungal disease epidemic in a major crop
- (2016) H. Charles J. Godfray et al. PHILOSOPHICAL TRANSACTIONS OF THE ROYAL SOCIETY B-BIOLOGICAL SCIENCES
- Plant Disease Detection by Imaging Sensors – Parallels and Specific Demands for Precision Agriculture and Plant Phenotyping
- (2016) Anne-Katrin Mahlein PLANT DISEASE
- Using Deep Learning for Image-Based Plant Disease Detection
- (2016) Sharada P. Mohanty et al. Frontiers in Plant Science
- Deep Neural Networks Based Recognition of Plant Diseases by Leaf Image Classification
- (2016) Srdjan Sladojevic et al. Computational Intelligence and Neuroscience
- Intelligent alerting for fruit-melon lesion image based on momentum deep learning
- (2015) Wenxue Tan et al. MULTIMEDIA TOOLS AND APPLICATIONS
- Deep learning
- (2015) Yann LeCun et al. NATURE
- Transfer Learning for Visual Categorization: A Survey
- (2015) Ling Shao et al. IEEE Transactions on Neural Networks and Learning Systems
- The PRISMA Statement for Reporting Systematic Reviews and Meta-Analyses of Studies That Evaluate Health Care Interventions: Explanation and Elaboration
- (2013) Alessandro Liberati ANNALS OF INTERNAL MEDICINE
- Externalising tacit knowledge of the systematic review process
- (2013) Sandra Camargo Pinto Ferraz Fabbri et al. IET Software
- Digital image processing techniques for detecting, quantifying and classifying plant diseases
- (2013) Jayme Garcia Arnal Barbedo SpringerPlus
- Plant Disease Diagnostic Capabilities and Networks
- (2009) Sally A. Miller et al. Annual Review of Phytopathology
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