Skyline variations allow estimating distance to trees on landscape photos using semantic segmentation-Reference-Cited by-同舟云学术

Skyline variations allow estimating distance to trees on landscape photos using semantic segmentation

Published:2022-09 Issue: Volume:70 Page:101757
ISSN:1574-9541
Container-title:Ecological Informatics
language:en
Short-container-title:Ecological Informatics

Author:

Martinez-Sanchez Laura,Borio Daniele,d'Andrimont Raphaël,van der Velde Marijn

Funder

European Commission Joint Research Centre

Publisher

Elsevier BV

Subject

Applied Mathematics,Computational Theory and Mathematics,Computer Science Applications,Ecological Modeling,Modeling and Simulation,Ecology,Ecology, Evolution, Behavior and Systematics

Reference53 articles.

1. Machine Learning Based Mountainous Skyline Detection and Visualgeo-Localization, Phdthesis;Ahmad,2017

2. Comparison of semantic segmentation approaches for horizon/sky line detection;Ahmad,2017

3. Resource efficient mountainous skyline extraction using shallow learning;Ahmad,2021

4. Land use/cover area frame survey (LUCAS 2006) - studies LOT 1;Aifantopoulou,2007

5. Statistics of atomic frequency standards;Allan;Proc. IEEE,1966

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