Related references
Note: Only part of the references are listed.Recognition of Apple Leaf Diseases using Deep Learning and Variances-Controlled Features Reduction
Muqadas Bin Tahir et al.
MICROPROCESSORS AND MICROSYSTEMS (2021)
Multi-Block Color-Binarized Statistical Images for Single-Sample Face Recognition
Insaf Adjabi et al.
SENSORS (2021)
VirLeafNet: Automatic analysis and viral disease diagnosis using deep-learning in Vigna mungo plant
Rakesh Chandra Joshi et al.
ECOLOGICAL INFORMATICS (2021)
Identification of disease using deep learning and evaluation of bacteriosis in peach leaf
Saumya Yadav et al.
ECOLOGICAL INFORMATICS (2021)
A deep learning approach to measure stress level in plants due to Nitrogen deficiency
Shiva Azimi et al.
MEASUREMENT (2021)
Plant diseases and pests detection based on deep learning: a review
Jun Liu et al.
PLANT METHODS (2021)
A deep learning approach for RGB image-based powdery mildew disease detection on strawberry leaves
Jaemyung Shin et al.
COMPUTERS AND ELECTRONICS IN AGRICULTURE (2021)
Identification of rice plant diseases using lightweight attention networks
Junde Chen et al.
EXPERT SYSTEMS WITH APPLICATIONS (2021)
Citrus pests classification using an ensemble of deep learning models
Morteza Khanramaki et al.
COMPUTERS AND ELECTRONICS IN AGRICULTURE (2021)
Recognition of rice leaf diseases and wheat leaf diseases based on multi-task deep transfer learning
Zhencun Jiang et al.
COMPUTERS AND ELECTRONICS IN AGRICULTURE (2021)
Rice leaf diseases prediction using deep neural networks with transfer learning
N. Krishnamoorthy et al.
ENVIRONMENTAL RESEARCH (2021)
A new Conv2D model with modified ReLU activation function for identification of disease type and severity in cucumber plant
Mohit Agarwal et al.
SUSTAINABLE COMPUTING-INFORMATICS & SYSTEMS (2021)
Applications of Computer Vision in Plant Pathology: A Survey
Siddharth Singh Chouhan et al.
ARCHIVES OF COMPUTATIONAL METHODS IN ENGINEERING (2020)
Deep Learning for Generic Object Detection: A Survey
Li Liu et al.
INTERNATIONAL JOURNAL OF COMPUTER VISION (2020)
Past, Present, and Future of Face Recognition: A Review
Insaf Adjabi et al.
ELECTRONICS (2020)
Use of deep learning techniques for identification of plant leaf stresses: A review
Serosh Karim Noon et al.
SUSTAINABLE COMPUTING-INFORMATICS & SYSTEMS (2020)
Plants Disease Identification and Classification Through Leaf Images: A Survey
Sukhvir Kaur et al.
ARCHIVES OF COMPUTATIONAL METHODS IN ENGINEERING (2019)
A comparative study of fine-tuning deep learning models for plant disease identification
Edna Chebet Too et al.
COMPUTERS AND ELECTRONICS IN AGRICULTURE (2019)
Rice Blast Disease Recognition Using a Deep Convolutional Neural Network
Wan-jie Liang et al.
SCIENTIFIC REPORTS (2019)
Visual Tea Leaf Disease Recognition Using a Convolutional Neural Network Model
Jing Chen et al.
SYMMETRY-BASEL (2019)
Plant disease identification from individual lesions and spots using deep learning
Jayme Garcia Arnal Barbedo
BIOSYSTEMS ENGINEERING (2019)
A Comparative Study of Deep CNN in Forecasting and Classifying the Macronutrient Deficiencies on Development of Tomato Plant
Trung-Tin Tran et al.
APPLIED SCIENCES-BASEL (2019)
AI-powered banana diseases and pest detection
Michael Gomez Selvaraj et al.
PLANT METHODS (2019)
Convolutional Neural Networks for the Automatic Identification of Plant Diseases
Justine Boulent et al.
FRONTIERS IN PLANT SCIENCE (2019)
A Unified Matrix-Based Convolutional Neural Network for Fine-Grained Image Classification of Wheat Leaf Diseases
Zhongqi Lin et al.
IEEE ACCESS (2019)
A Computational Procedure for the Recognition and Classification of Maize Leaf Diseases Out of Healthy Leaves Using Convolutional Neural Networks
Malusi Sibiya et al.
AGRIENGINEERING (2019)
Identification of Apple Leaf Diseases Based on Deep Convolutional Neural Networks
Bin Liu et al.
SYMMETRY-BASEL (2018)
Deep learning models for plant disease detection and diagnosis
Konstantinos P. Ferentinos
COMPUTERS AND ELECTRONICS IN AGRICULTURE (2018)
An explainable deep machine vision framework for plant stress phenotyping
Sambuddha Ghosal et al.
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA (2018)
Aerial Images and Convolutional Neural Network for Cotton Bloom Detection
Rui Xu et al.
FRONTIERS IN PLANT SCIENCE (2018)
Bacterial Foraging Optimization Based Radial Basis Function Neural Network (BRBFNN) for Identification and Classification of Plant Leaf Diseases: An Automatic Approach Towards Plant Pathology
Siddharth Singh Chouhan et al.
IEEE ACCESS (2018)
Identification of Maize Leaf Diseases Using Improved Deep Convolutional Neural Networks
Xihai Zhang et al.
IEEE ACCESS (2018)
A recognition method for cucumber diseases using leaf symptom images based on deep convolutional neural network
Juncheng Ma et al.
COMPUTERS AND ELECTRONICS IN AGRICULTURE (2018)
CCDF: Automatic system for segmentation and recognition of fruit crops diseases based on correlation coefficient and deep CNN features
Muhammad Attique Khan et al.
COMPUTERS AND ELECTRONICS IN AGRICULTURE (2018)
Deep leaning approach with colorimetric spaces and vegetation indices for vine diseases detection in UAV images
Mohamed Kerkech et al.
COMPUTERS AND ELECTRONICS IN AGRICULTURE (2018)
Deep convolution neural network for image recognition
Boukaye Boubacar Traore et al.
ECOLOGICAL INFORMATICS (2018)
Can Deep Learning Identify Tomato Leaf Disease?
Keke Zhang et al.
ADVANCES IN MULTIMEDIA (2018)
Plant identification using deep neural networks via optimization of transfer learning parameters
Mostafa Mehdipour Ghazi et al.
NEUROCOMPUTING (2017)
Identification of rice diseases using deep convolutional neural networks
Yang Lu et al.
NEUROCOMPUTING (2017)
Automated Identification of Northern Leaf Blight-Infected Maize Plants from Field Imagery Using Deep Learning
Chad DeChant et al.
PHYTOPATHOLOGY (2017)
A Robust Deep-Learning-Based Detector for Real-Time Tomato Plant Diseases and Pests Recognition
Alvaro Fuentes et al.
SENSORS (2017)
Deep Learning for Image-Based Cassava Disease Detection
Amanda Ramcharan et al.
FRONTIERS IN PLANT SCIENCE (2017)
X-FIDO: An Effective Application for Detecting Olive Quick Decline Syndrome with Deep Learning and Data Fusion
Albert C. Cruz et al.
FRONTIERS IN PLANT SCIENCE (2017)
iPathology: Robotic Applications and Management of Plants and Plant Diseases
Yiannis Ampatzidis et al.
SUSTAINABILITY (2017)
Automatic Image-Based Plant Disease Severity Estimation Using Deep Learning
Guan Wang et al.
COMPUTATIONAL INTELLIGENCE AND NEUROSCIENCE (2017)
Deep machine learning provides state-of-the-art performance in image-based plant phenotyping
Michael P. Pound et al.
GIGASCIENCE (2017)
CNN Design for Real-Time Traffic Sign Recognition
Alexander Shustanov et al.
3RD INTERNATIONAL CONFERENCE INFORMATION TECHNOLOGY AND NANOTECHNOLOGY (ITNT-2017) (2017)
Counting Apples and Oranges With Deep Learning: A Data-Driven Approach
Steven W. Chen et al.
IEEE ROBOTICS AND AUTOMATION LETTERS (2017)
An in-field automatic wheat disease diagnosis system
Jiang Lu et al.
COMPUTERS AND ELECTRONICS IN AGRICULTURE (2017)
High throughput phenotyping to accelerate crop breeding and monitoring of diseases in the field
Nadia Shakoor et al.
CURRENT OPINION IN PLANT BIOLOGY (2017)
Automatic plant disease diagnosis using mobile capture devices, applied on a wheat use case
Alexander Johannes et al.
COMPUTERS AND ELECTRONICS IN AGRICULTURE (2017)
Deep Learning for Tomato Diseases: Classification and Symptoms Visualization
Mohammed Brahimi et al.
APPLIED ARTIFICIAL INTELLIGENCE (2017)
Intelligent alerting for fruit-melon lesion image based on momentum deep learning
Wenxue Tan et al.
MULTIMEDIA TOOLS AND APPLICATIONS (2016)
Plant species classification using deep convolutional neural network
Mads Dyrmann et al.
BIOSYSTEMS ENGINEERING (2016)
A review on the main challenges in automatic plant disease identification based on visible range images
Jayme Garcia Arnal Barbedo
BIOSYSTEMS ENGINEERING (2016)
In-field cotton detection via region-based semantic image segmentation
Yanan Li et al.
COMPUTERS AND ELECTRONICS IN AGRICULTURE (2016)
Automatic moth detection from trap images for pest management
Weiguang Ding et al.
COMPUTERS AND ELECTRONICS IN AGRICULTURE (2016)
DeepFruits: A Fruit Detection System Using Deep Neural Networks
Inkyu Sa et al.
SENSORS (2016)
Machine Learning for High-Throughput Stress Phenotyping in Plants
Arti Singh et al.
TRENDS IN PLANT SCIENCE (2016)
Using Deep Learning for Image-Based Plant Disease Detection
Sharada P. Mohanty et al.
FRONTIERS IN PLANT SCIENCE (2016)
Deep Neural Networks Based Recognition of Plant Diseases by Leaf Image Classification
Srdjan Sladojevic et al.
COMPUTATIONAL INTELLIGENCE AND NEUROSCIENCE (2016)
Leaf Doctor: A New Portable Application for Quantifying Plant Disease Severity
Sarah J. Pethybridge et al.
PLANT DISEASE (2015)
Health and Economic Burden of Obesity in Elderly Individuals with Asthma in the United States
Ruchit Shah et al.
POPULATION HEALTH MANAGEMENT (2015)
The potential of automatic methods of classification to identify leaf diseases from multispectral images
Sabine D. Bauer et al.
PRECISION AGRICULTURE (2011)
Plant Disease Severity Estimated Visually, by Digital Photography and Image Analysis, and by Hyperspectral Imaging
C. H. Bock et al.
CRITICAL REVIEWS IN PLANT SCIENCES (2010)
A Survey on Transfer Learning
Sinno Jialin Pan et al.
IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING (2010)
Application of artificial neural network for detecting Phalaenopsis seedling diseases using color and texture features
Kuo-Yi Huang
COMPUTERS AND ELECTRONICS IN AGRICULTURE (2007)