Sustainable Development of Rural Areas: Machine Learning for Semantic Segmentation of Agricultural Fields-Reference-Cited by-同舟云学术

Sustainable Development of Rural Areas: Machine Learning for Semantic Segmentation of Agricultural Fields

Published:2024 Issue: Volume: Page:183-195
ISSN:2522-8595
Container-title:EAI/Springer Innovations in Communication and Computing
language:en
Short-container-title:

Author:

Shramenko Vladyslav^ORCID,Shramenko Natalya^ORCID,Hupfer Christoph^ORCID

Publisher

Springer Nature Switzerland

Link

https://link.springer.com/content/pdf/10.1007/978-3-031-56533-5_14

Reference32 articles.

1. European Parliamentary Research Service (EPRS). The future of the EU’s rural areas. Available online: https://epthinktank.eu/2022/03/14/the-future-of-the-eus-rural-areas/, last accessed 2022/12/27.

2. World Bank Data: Rural population (% of total population) - European Union. Available online: https://data.worldbank.org/indicator/SP.RUR.TOTL.ZS?locations=EU, last accessed 2022/12/27.

3. Jankiewicz, S., Mierzwa, D.: Renewable energy sources as a basis for sustainable development of rural areas. Ekonomia i Środowisko. Tom 1, pp. 191—197. (2018) http://yadda.icm.edu.pl/baztech/element/bwmeta1.element.baztech-285b93f8-0eb0-4410-9685-5eaf80e553f1

4. Raluca Crina Vasile Rusu, Mihaela Neculiță, Dragoș Cristea, Alina Mogodan, Ştefan Petrea, Ira Simionov: Sustainable development of rural areas of south-east region of Romania. Scientific Papers Series Management, Economic Engineering in Agriculture and Rural Development Vol. 20, Issue 2, pp. 523–529. (2020).

5. Häußler, E., Blaszczyk R., Hupfer, C.: Den Fußverkehr in Städten fördern: Partizipative Forschung im Reallabor GO Karlsruhe; https://doi.org/10.14512/gaia.28.4.16 Corpus ID: 212761699, Published 19 December 2019 Gaia-ecological Perspectives for Science and Society. (2019).