Clustering of crop phenotypes by means of hyperspectral signatures using artificial neural networks-Reference-Cited by-同舟云学术

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Clustering of crop phenotypes by means of hyperspectral signatures using artificial neural networks

Published:2010-06 Issue: Volume: Page:
ISSN:
Container-title:2010 2nd Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing
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Author:

Seiffert Udo¹,Bollenbeck Felix¹,Mock Hans-Peter²,Matros Andrea²

Affiliation:

1. Fraunhofer Institute for Factory Operation and Automation (IFF) Magdeburg, Germany

2. Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben, Germany

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx5/5587708/5594823/05594947.pdf?arnumber=5594947

Cited by 13 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Non‐invasive assessment of cultivar and sex of Cannabis sativa L. by means of hyperspectral measurement;Plant-Environment Interactions;2023-08-17

2. Performance Comparison of Learning Methods for Soil Parameter Estimation using Hyperspectral Data;2022 8th International Conference on Signal Processing and Communication (ICSC);2022-12-01

3. A Review on Sensing Technologies for High-Throughput Plant Phenotyping;IEEE Open Journal of Instrumentation and Measurement;2022

4. A hyperspectral image classification algorithm based on atrous convolution;EURASIP Journal on Wireless Communications and Networking;2019-12

5. Evaluating maize phenotype dynamics under drought stress using terrestrial lidar;Plant Methods;2019-02-04

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