K. Kraft

发表

Towards operational phytoplankton recognition with automated high-throughput imaging, near-real-time data processing, and convolutional neural networks

H. Haario, T. Eerola, H. Kälviäinen, 2022, Frontiers in Marine Science.

Dataset from a mesocosm experiment on brownification in the Baltic Sea

J. Seppälä, J. Norkko, A. Lewandowska, 2022, Data in Brief.

First Application of IFCB High-Frequency Imaging-in-Flow Cytometry to Investigate Bloom-Forming Filamentous Cyanobacteria in the Baltic Sea

S. Lehtinen, J. Seppälä, H. Kuosa, 2021, Frontiers in Marine Science.

Trait response of three Baltic Sea spring dinoflagellates to temperature, salinity, and light gradients

T. Tamminen, P. Ylöstalo, L. Haraguchi, 2023, Frontiers in Marine Science.

Survey of Automatic Plankton Image Recognition: Challenges, Existing Solutions and Future Perspectives

T. Eerola, H. Kälviäinen, L. Lensu, 2023, Artif. Intell. Rev..

Towards operational phytoplankton recognition with automated high-throughput imaging and compact convolutional neural networks

Heikki Haario, Tuomas Eerola, Heikki Kälviäinen, 2020 .

Shipping and algae emissions have a major impact on ambient air mixing ratios of NMHCs and methanethiol on Utö island in the Baltic Sea

H. Hakola, J. Jalkanen, L. Laakso, 2022 .

Toward phytoplankton parasite detection using autoencoders

T. Eerola, H. Kälviäinen, L. Lensu, 2023, Machine Vision and Applications.