Automatic late blight lesion recognition and severity quantification based on field imagery of diverse potato genotypes by deep learning

Deep convolutional neural networks for image-based Convolvulus sepium detection in sugar beet fields

(2020) Junfeng Gao et al.   Plant Methods

Hyperspectral Measurements Enable Pre-Symptomatic Detection and Differentiation of Contrasting Physiological Effects of Late Blight and Early Blight in Potato

(2020) Kaitlin M. Gold et al.   Remote Sensing

Potato Late Blight Detection at the Leaf and Canopy Levels Based in the Red and Red-Edge Spectral Regions

(2020) Claudio Ignacio Fernández et al.   Remote Sensing

Practical Recommendations for Hyperspectral and Thermal Proximal Disease Sensing in Potato and Leek Fields

(2020) Simon Appeltans et al.   Remote Sensing

A review of computer vision technologies for plant phenotyping

(2020) Zhenbo Li et al.   COMPUTERS AND ELECTRONICS IN AGRICULTURE

Potato Virus Y Detection in Seed Potatoes Using Deep Learning on Hyperspectral Images

(2019) Gerrit Polder et al.   Frontiers in Plant Science

Feasibility of Unmanned Aerial Vehicle Optical Imagery for Early Detection and Severity Assessment of Late Blight in Potato

(2019) Marston Héracles Domingues Franceschini et al.   Remote Sensing

High-Throughput Field-Phenotyping Tools for Plant Breeding and Precision Agriculture

(2019) Aakash Chawade et al.   Agronomy-Basel

Angle estimation between plant parts for grasp optimisation in harvest robots

(2019) Ruud Barth et al.   BIOSYSTEMS ENGINEERING

Quantitative Phenotyping of Northern Leaf Blight in UAV Images Using Deep Learning

(2019) Ethan L. Stewart et al.   Remote Sensing

In-Field Detection and Quantification of Septoria Tritici Blotch in Diverse Wheat Germplasm Using Spectral–Temporal Features

(2019) Jonas Anderegg et al.   Frontiers in Plant Science

RootNav 2.0: Deep learning for automatic navigation of complex plant root architectures

(2019) Robail Yasrab et al.   GigaScience

Millimeter-Level Plant Disease Detection From Aerial Photographs via Deep Learning and Crowdsourced Data

(2019) Tyr Wiesner-Hanks et al.   Frontiers in Plant Science

Recognising weeds in a maize crop using a random forest machine-learning algorithm and near-infrared snapshot mosaic hyperspectral imagery

(2018) Junfeng Gao et al.   BIOSYSTEMS ENGINEERING

Fusion of pixel and object-based features for weed mapping using unmanned aerial vehicle imagery

(2018) Junfeng Gao et al.   International Journal of Applied Earth Observation and Geoinformation

Ranking Quantitative Resistance to Septoria tritici Blotch in Elite Wheat Cultivars Using Automated Image Analysis

(2018) Petteri Karisto et al.   PHYTOPATHOLOGY

The use of plant models in deep learning: an application to leaf counting in rosette plants

(2018) Jordan Ubbens et al.   Plant Methods

Hyperspectral Sensors and Imaging Technologies in Phytopathology: State of the Art

(2018) A.-K. Mahlein et al.   Annual Review of Phytopathology

Evaluating Late Blight Severity in Potato Crops Using Unmanned Aerial Vehicles and Machine Learning Algorithms

(2018) Julio Duarte-Carvajalino et al.   Remote Sensing

Hyperspectral Canopy Sensing of Wheat Septoria Tritici Blotch Disease

(2018) Kang Yu et al.   Frontiers in Plant Science

SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation

(2017) Vijay Badrinarayanan et al.   IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE

Field phenotyping system for the assessment of potato late blight resistance using RGB imagery from an unmanned aerial vehicle

(2016) Ryo Sugiura et al.   BIOSYSTEMS ENGINEERING

A new automatic method for disease symptom segmentation in digital photographs of plant leaves

(2016) Jayme Garcia Arnal Barbedo   EUROPEAN JOURNAL OF PLANT PATHOLOGY

Image-Based Quantification of Plant Immunity and Disease

(2016) Bradley Laflamme et al.   MOLECULAR PLANT-MICROBE INTERACTIONS

Plant Disease Detection by Imaging Sensors – Parallels and Specific Demands for Precision Agriculture and Plant Phenotyping

(2016) Anne-Katrin Mahlein   PLANT DISEASE

Overview and Breeding Strategies of Table Potato Production in Sweden and the Fennoscandian Region

(2016) Dennis Eriksson et al.   POTATO RESEARCH

Localization and Classification of Paddy Field Pests using a Saliency Map and Deep Convolutional Neural Network

(2016) Ziyi Liu et al.   Scientific Reports

Deep learning

(2015) Yann LeCun et al.   NATURE

Application of hyperspectral imaging technology to discriminate different geographical origins of Jatropha curcas L. seeds

(2013) Junfeng Gao et al.   COMPUTERS AND ELECTRONICS IN AGRICULTURE

Crop losses due to diseases and their implications for global food production losses and food security

(2012) Serge Savary et al.   Food Security

An image-processing based algorithm to automatically identify plant disease visual symptoms

(2008) A. Camargo et al.   BIOSYSTEMS ENGINEERING