A Computational Approach to Bio-optical Functional Group Classification of Phytoplankton in Inland Waters
Downloads:
Naik, P., Pölönen, I., & Salmi, P. (2024). A Computational Approach to Bio-optical Functional Group Classification of Phytoplankton in Inland Waters. In Winter Satellite Workshop 2024. Aalto-yliopisto. https://spaceworkshop.fi/program2024.html
Date
2024Copyright
© 2024 the Authors
Publisher
Aalto-yliopistoConference
Winter Satellite WorkshopIs part of publication
Winter Satellite Workshop 2024Keywords
Original source
https://spaceworkshop.fi/program2024.htmlPublication in research information system
https://converis.jyu.fi/converis/portal/detail/Publication/207738940
Metadata
Show full item recordCollections
Related funder(s)
Research Council of FinlandFunding program(s)
Academy Research Fellow, AoFLicense
Related items
Showing items with similar title or keywords.
-
Updating strategies for distance based classification model with recursive least squares
Raita-Hakola, Anna-Maria; Pölönen, Ilkka (Copernicus Publications, 2022)The idea is to create a self-learning Minimal Learning Machine (MLM) model that is computationally efficient, easy to implement and performs with high accuracy. The study has two hypotheses. Experiment A examines the ... -
Browning-induced changes in trophic functioning of planktonic food webs in temperate and boreal lakes : insights from fatty acids
Strandberg, Ursula; Hiltunen, Minna; Creed, Irena F.; Arts, Michael T.; Kankaala, Paula (Springer, 2023)The effects of lake browning on trophic functioning of planktonic food webs are not fully understood. We studied the effects of browning on the response patterns of polyunsaturated fatty acids and n−3/n−6 ratio in seston ... -
A practical approach to improve the statistical performance of surface water monitoring networks
Kotamäki, Niina; Järvinen, Marko; Kauppila, Pirkko; Korpinen, Samuli; Lensu, Anssi; Malve, Olli; Mitikka, Sari; Silander, Jari; Kettunen, Juhani (Springer Netherlands, 2019)The representativeness of aquatic ecosystem monitoring and the precision of the assessment results are of high importance when implementing the EU’s Water Framework Directive that aims to secure a good status of waterbodies ... -
Approaches and challenges of automatic vulnerability classification using natural language processing and machine learning techniques
Jormakka, Ossi (2019)Automatisoitu haavoittuvuuksien etsiminen ja haavoittuvuuksien yksityiskohtien ennustaminen voi auttaa asiantuntijoita priorisoimaan ohjelmistovirheitä, joka voi johtaa nopeampaan virheenkorjaukseen. Tässä työssä käytettiin ... -
Resolving phytoplankton pigments from spectral images using convolutional neural networks
Salmi, Pauliina; Pölönen, Ilkka; Beckmann, Daniel Atton; Calderini, Marco L.; May, Linda; Olszewska, Justyna; Perozzi, Laura; Pääkkönen, Salli; Taipale, Sami; Hunter, Peter (John Wiley & Sons, 2024)Motivated by the need for rapid and robust monitoring of phytoplankton in inland waters, this article introduces a protocol based on a mobile spectral imager for assessing phytoplankton pigments from water samples. The ...