Journal ArticleDOI
Robust fitting of fluorescence spectra for pre-symptomatic wheat leaf rust detection with Support Vector Machines
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TLDR
The described method is of general interest for pre-symptomatic pathogen detection based on fluorescence spectra and demonstrated that the achieved classification accuracy could be attained on the second day after inoculation, before any visible symptoms appeared.About:
This article is published in Computers and Electronics in Agriculture.The article was published on 2011-11-01. It has received 77 citations till now.read more
Citations
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Pattern Recognition and Machine Learning
TL;DR: Probability distributions of linear models for regression and classification are given in this article, along with a discussion of combining models and combining models in the context of machine learning and classification.
Journal ArticleDOI
Field high-throughput phenotyping: the new crop breeding frontier
José Luis Araus,Jill E. Cairns +1 more
TL;DR: Recent advances in field HTPPs are reviewed, which should combine at an affordable cost, high capacity for data recording, scoring and processing, and non-invasive remote sensing methods, together with automated environmental data collection.
Journal ArticleDOI
A review of imaging techniques for plant phenotyping.
Lei Li,Qin Zhang,Danfeng Huang +2 more
TL;DR: A brief review on a variety of imaging methodologies used to collect data for quantitative studies of complex traits related to the growth, yield and adaptation to biotic or abiotic stress in plant phenotyping.
Journal ArticleDOI
Field Scanalyzer: An automated robotic field phenotyping platform for detailed crop monitoring
TL;DR: A fully automated robotic field phenotyping platform with a dedicated sensor array that may be accurately positioned in three dimensions and mounted on fixed rails has been established, to facilitate continual and high-throughput monitoring of crop performance.
Journal ArticleDOI
A review of advanced machine learning methods for the detection of biotic stress in precision crop protection
TL;DR: A short introduction into machine learning is given, its potential for precision crop protection is analyzed and an overview of instructive examples from different fields of precision agriculture is provided.
References
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Book
Genetic algorithms in search, optimization, and machine learning
TL;DR: In this article, the authors present the computer techniques, mathematical tools, and research results that will enable both students and practitioners to apply genetic algorithms to problems in many fields, including computer programming and mathematics.
Journal ArticleDOI
LIBSVM: A library for support vector machines
Chih-Chung Chang,Chih-Jen Lin +1 more
TL;DR: Issues such as solving SVM optimization problems theoretical convergence multiclass classification probability estimates and parameter selection are discussed in detail.
Book
Convex Optimization
Stephen Boyd,Lieven Vandenberghe +1 more
TL;DR: In this article, the focus is on recognizing convex optimization problems and then finding the most appropriate technique for solving them, and a comprehensive introduction to the subject is given. But the focus of this book is not on the optimization problem itself, but on the problem of finding the appropriate technique to solve it.
Statistical learning theory
TL;DR: Presenting a method for determining the necessary and sufficient conditions for consistency of learning process, the author covers function estimates from small data pools, applying these estimations to real-life problems, and much more.
Book
Pattern Recognition and Machine Learning
TL;DR: Probability Distributions, linear models for Regression, Linear Models for Classification, Neural Networks, Graphical Models, Mixture Models and EM, Sampling Methods, Continuous Latent Variables, Sequential Data are studied.