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Ml-Mining: Machine Learning Surrogate Modeling for Environmental Risk Assessment and Water Quality Prediction at Mining SitesGeological Survey of Finland2023Mining the unknown part of fungal genomes by combining machine learning with multi-omics and functional characterization, JGI CSPUniversity of Helsinki2021The Multi-source and Multi-scale Earth observation and Novel Machine Learning Methods for Mineral Exploration and Mine Site Monitoring (MultiMiner)Geological Survey of Finland2023Advanced machine learning methods for biomonitoring (AMBI)Finnish Environment Institute2019Life in the fast lane: Computer vision and machine learning to unveil biodiversity dynamics and ecosystem responses in the planktonic realm - FASTVISIONFinnish Environment Institute2019Taxa Identification with Machine Learning Enhanced by DNA Metabarcoding (TIMED)Finnish Environment Institute2020
Ml-Mining: Machine Learning Surrogate Modeling for Environmental Risk Assessment and Water Quality Prediction at Mining Sites
2023
Mining the unknown part of fungal genomes by combining machine learning with multi-omics and functional characterization, JGI CSP
2021
The Multi-source and Multi-scale Earth observation and Novel Machine Learning Methods for Mineral Exploration and Mine Site Monitoring (MultiMiner)
2023
Advanced machine learning methods for biomonitoring (AMBI)
2019
Life in the fast lane: Computer vision and machine learning to unveil biodiversity dynamics and ecosystem responses in the planktonic realm - FASTVISION
2019
Taxa Identification with Machine Learning Enhanced by DNA Metabarcoding (TIMED)
2020