首页|Technical University Cluj Napoca Details Findings in Machine Learning (Using Machine Learning Algorithms for Natural Habitats Assessment)

Technical University Cluj Napoca Details Findings in Machine Learning (Using Machine Learning Algorithms for Natural Habitats Assessment)

扫码查看
Investigators discuss new findings in Machine Learning. According to news reporting originating from Baia Mare, Romania, by NewsRx correspondents, research stated, “The potential of AI to process and interpret large volumes of data can provide researchers with a powerful tool to understand and monitor biodiversity on a global scale. In this paper we aimed to identify dominant individual plant species in natural protected habitats.” Financial support for this research came from European Regional Development Fund through the Romania’s Competitiveness Operational Program 2014-2020. Our news editors obtained a quote from the research from Technical University Cluj Napoca, “Mapping the dominant species from the targeted natural habitats was followed by testing machine learning algorithm for differentiating similar species using satellite images. In the end we validated the data generated by machine learning algorithms through extensive field observations. Using the Sentinel-2 mission 10m resolution data and comprehensive field mapping we managed to see different phenology variations between diverse types of plant communities. Using the NDVI and NDII vegetation indexes and Random Forest algorithm during the dominant species phenology stages for each consecutive 10-day periods between May 1st and September 10th, revealed distinct responses to climate fluctuations and environmental factors. The natural habitats different signatures are strongly influenced by their ecological and conservation status and are not yet suitable for identification, but could help improve AI’s automatic detection for multiannual analysis if a favorable conservation trend is reached.”

Baia MareRomaniaEuropeAlgorithmsCyborgsEmerging TechnologiesMachine LearningTechnical University Cluj Napoca

2024

Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

ISSN:
年,卷(期):2024.(Feb.7)
  • 26