A Deep Learning-Based Approach for Automated Yellow Rust Disease Detection from High-Resolution Hyperspectral UAV Images
Published 2019 View Full Article
- Home
- Publications
- Publication Search
- Publication Details
Title
A Deep Learning-Based Approach for Automated Yellow Rust Disease Detection from High-Resolution Hyperspectral UAV Images
Authors
Keywords
-
Journal
Remote Sensing
Volume 11, Issue 13, Pages 1554
Publisher
MDPI AG
Online
2019-07-01
DOI
10.3390/rs11131554
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- Early Visual Detection of Wheat Stripe Rust Using Visible/Near-Infrared Hyperspectral Imaging
- (2019) Zhifeng Yao et al. SENSORS
- The global burden of pathogens and pests on major food crops
- (2019) Serge Savary et al. Nature Ecology & Evolution
- Early optical detection of infection with brown rust in winter wheat by chlorophyll fluorescence excitation spectra
- (2018) Ylva Katharina Tischler et al. COMPUTERS AND ELECTRONICS IN AGRICULTURE
- 3-D Deep Learning Approach for Remote Sensing Image Classification
- (2018) Amina Ben Hamida et al. IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
- Wavelet-Based Rust Spectral Feature Set (WRSFs): A Novel Spectral Feature Set Based on Continuous Wavelet Transformation for Tracking Progressive Host–Pathogen Interaction of Yellow Rust on Wheat
- (2018) Yue Shi et al. Remote Sensing
- Spectral and Spatial Classification of Hyperspectral Images Based on Random Multi-Graphs
- (2018) Feng Gao et al. Remote Sensing
- A Deep Learning Approach to UAV Image Multilabeling
- (2017) Abdallah Zeggada et al. IEEE Geoscience and Remote Sensing Letters
- Hyperspectral Imaging: A Review on UAV-Based Sensors, Data Processing and Applications for Agriculture and Forestry
- (2017) Telmo Adão et al. Remote Sensing
- Random forest in remote sensing: A review of applications and future directions
- (2016) Mariana Belgiu et al. ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING
- Plant Disease Detection by Imaging Sensors – Parallels and Specific Demands for Precision Agriculture and Plant Phenotyping
- (2016) Anne-Katrin Mahlein PLANT DISEASE
- Deep Learning Based Oil Palm Tree Detection and Counting for High-Resolution Remote Sensing Images
- (2016) Weijia Li et al. Remote Sensing
- Spectral–Spatial Classification of Hyperspectral Images With a Superpixel-Based Discriminative Sparse Model
- (2015) Leyuan Fang et al. IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
- Continuous and long-term measurements of reflectance and sun-induced chlorophyll fluorescence by using novel automated field spectroscopy systems
- (2015) S. Cogliati et al. REMOTE SENSING OF ENVIRONMENT
- Research investment implications of shifts in the global geography of wheat stripe rust
- (2015) Jason M. Beddow et al. Nature Plants
- Deep Learning-Based Classification of Hyperspectral Data
- (2014) Yushi Chen et al. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
- Evaluating the Effect of Different Wheat Rust Disease Symptoms on Vegetation Indices Using Hyperspectral Measurements
- (2014) Davoud Ashourloo et al. Remote Sensing
- Spectral–Spatial Classification of Multispectral Images Using Kernel Feature Space Representation
- (2013) Sergio Bernabe et al. IEEE Geoscience and Remote Sensing Letters
- Spatial-Spectral Kernel Sparse Representation for Hyperspectral Image Classification
- (2013) Jianjun Liu et al. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
- Development of spectral indices for detecting and identifying plant diseases
- (2012) A.-K. Mahlein et al. REMOTE SENSING OF ENVIRONMENT
- Global status of stripe rust: a review of historical and current threats
- (2011) Colin R. Wellings EUPHYTICA
- A comparison of pixel-based and object-based image analysis with selected machine learning algorithms for the classification of agricultural landscapes using SPOT-5 HRG imagery
- (2011) Dennis C. Duro et al. REMOTE SENSING OF ENVIRONMENT
- A review of advanced techniques for detecting plant diseases
- (2010) Sindhuja Sankaran et al. COMPUTERS AND ELECTRONICS IN AGRICULTURE
- Plant Disease Severity Estimated Visually, by Digital Photography and Image Analysis, and by Hyperspectral Imaging
- (2010) C. H. Bock et al. CRITICAL REVIEWS IN PLANT SCIENCES
- Satellite Remote Sensing of Wheat Infected byWheat streak mosaic virus
- (2010) M. Mirik et al. PLANT DISEASE
- Chlorophyll fluorescence imaging as tool for understanding the impact of fungal diseases on plant performance: a phenomics perspective
- (2009) Julie D. Scholes et al. FUNCTIONAL PLANT BIOLOGY
- Remote sensing of solar-induced chlorophyll fluorescence: Review of methods and applications
- (2009) M. Meroni et al. REMOTE SENSING OF ENVIRONMENT
- Imaging chlorophyll fluorescence with an airborne narrow-band multispectral camera for vegetation stress detection
- (2009) P.J. Zarco-Tejada et al. REMOTE SENSING OF ENVIRONMENT
- Evaluating ten spectral vegetation indices for identifying rust infection in individual wheat leaves
- (2008) R. Devadas et al. PRECISION AGRICULTURE
- The use of remote sensing in light use efficiency based models of gross primary production: A review of current status and future requirements
- (2007) Thomas Hilker et al. SCIENCE OF THE TOTAL ENVIRONMENT
Become a Peeref-certified reviewer
The Peeref Institute provides free reviewer training that teaches the core competencies of the academic peer review process.
Get StartedAsk a Question. Answer a Question.
Quickly pose questions to the entire community. Debate answers and get clarity on the most important issues facing researchers.
Get Started