Hyperspectral remote sensing of plant biochemistry using Bayesian model averaging with variable and band selection

By Kaiguang Zhao, Denis Ribeiro do Valle, Sorin C. Popescu, Xuesong Zhang, Bani K. Mallick. 2013

157 citations recorded by the source corpus.

Subfields: Analytical Chemistry, Ecology, Plant Science

View Paper: https://www.semanticscholar.org/paper/91ed2e12e9335c0227c894a559e364183fbf48e2

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Analytical Chemistry

1. Lei Li
2. Danfeng Huang
3. Qin Zhang

In Ecology

1. Jose A. Jiménez-Berni
2. Lei Li
3. David Deery
4. Xavier Sirault
5. Robert Furbank
6. H. Jones
7. Danfeng Huang
8. Qin Zhang

In Plant Science

1. Jose A. Jiménez-Berni
2. Lei Li
3. Robert Furbank
4. H. Jones
5. Danfeng Huang
6. Qin Zhang
7. J. Royo
8. Luis Gonzaga Santesteban

Citations in the corpus

• A Review of Imaging Techniques for Plant Phenotyping (2014, methodology): “These appropriate mathematical treatments and algorithms include 2D correlation plots [136], partial least squares regression [137,138], principal components analysis [139], support vector machines [140], neural networks [141] and other machine learning approaches.”
• Proximal Remote Sensing Buggies and Potential Applications for Field-Based Phenotyping (2014, methodology): “These include the use of 2D correlation plots [66], partial least squares regression [67,68], principal components analysis [65], support vector machines (SVM) [69], neural networks [70] and other machine learning approaches for stress detection.”