Estimation of the Botanical Composition of Clover-Grass Leys from RGB Images Using Data Simulation and Fully Convolutional Neural Networks-Reference-Cited by-同舟云学术

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Estimation of the Botanical Composition of Clover-Grass Leys from RGB Images Using Data Simulation and Fully Convolutional Neural Networks

Published:2017-12-17 Issue:12 Volume:17 Page:2930
ISSN:1424-8220
Container-title:Sensors
language:en
Short-container-title:Sensors

Author:

Skovsen Søren,Dyrmann Mads,Mortensen Anders,Steen Kim,Green Ole,Eriksen Jørgen,Gislum René,Jørgensen Rasmus,Karstoft Henrik

Publisher

MDPI AG

Subject

Electrical and Electronic Engineering,Biochemistry,Instrumentation,Atomic and Molecular Physics, and Optics,Analytical Chemistry

Link

http://www.mdpi.com/1424-8220/17/12/2930/pdf

Reference23 articles.

1. Complementary effects of red clover inclusion in ryegrass-white clover swards for grazing and cutting

2. Yield and stability of yield of single- and multi-clover grass-clover swards in two contrasting temperate environments

3. Forage Legumes for Grazing and Conserving in Ruminant Production Systems

4. Strong mixture effects among four species in fertilized agricultural grassland led to persistent and consistent transgressive overyielding

5. Nitrogen fertilization of grass/clover swards under cutting or grazing by dairy cows;Egaard;Acta Agric. Scand. Sect. B—Soil Plant Sci.,2009

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1. Classifying Stand Compositions in Clover Grass Based on High-Resolution Multispectral UAV Images;Remote Sensing;2024-07-22

2. Quantification of species composition in grass-clover swards using RGB and multispectral UAV imagery and machine learning;Frontiers in Plant Science;2024-06-19

3. Clover Dry Matter Predictor Based on Semantic Segmentation Network and Random Forest;Applied Sciences;2023-10-26

4. The potential of remote sensing of cover crops to benefit sustainable and precision fertilization;Science of The Total Environment;2023-09

5. EasyDAM_V3: Automatic Fruit Labeling Based on Optimal Source Domain Selection and Data Synthesis via a Knowledge Graph;Plant Phenomics;2023-01

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