Spectral filter design based on in-field hyperspectral imaging and machine learning for mango ripeness estimation-Reference-Cited by-同舟云学术

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Spectral filter design based on in-field hyperspectral imaging and machine learning for mango ripeness estimation

Published:2019-09 Issue: Volume:164 Page:104890
ISSN:0168-1699
Container-title:Computers and Electronics in Agriculture
language:en
Short-container-title:Computers and Electronics in Agriculture

Author:

Gutiérrez Salvador,Wendel Alexander,Underwood James

Funder

Australian Centre for Field Robotics

Publisher

Elsevier BV

Subject

Horticulture,Computer Science Applications,Agronomy and Crop Science,Forestry

Reference54 articles.

1. Allied Vision Technologies GmbH. Prosilica GT3300 specifications. (Accessed: 2018-11-21).

2. Manipulation of mango fruit dry matter content to improve eating quality;Anderson;Sci. Hortic.,2017

3. Hyperspectral imaging: a novel approach for plant root phenotyping;Bodner;Plant Methods,2018

4. Hyperspectral band selection based on parallel particle swarm optimization and impurity function band prioritization schemes;Chang;J. Appl. Remote Sens.,2014

5. Proximal remote sensing buggies and potential applications for field-based phenotyping;Deery;Agronomy,2014

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