Finnish Environment Institute | Suomen ympäristökeskus | Finlands miljöcentral

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Advanced machine learning methods for biomonitoring (AMBI)

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Basic project information

Project description

I will develop machine learning algorithms to conquer challenges typically encountered automated image-based identification in biomonitoring. The considered challenges are i) unbalanced occurrence of different taxa, while most interesting taxa are rare, ii) variations in imaging conditions, which may harm identification accuracy, iii) detection of rare or invasive taxa that are absent in previously collected datasets, and iv) hierarchical nature of the identification task. I will apply state-of-the-art machine learning techniques and propose improvements to them to tackle the challenges.

Publications

Jenni Raitoharju and Kristian Meissner, On Confidences and Their Use in (Semi-)Automatic Taxa Identification, Accepted to IEEE Symposium Series in Computational Intelligence 2019.

More information

Senior Research Scientist Jenni Raitoharju

Published 2019-10-15 at 16:54, updated 2019-10-15 at 17:30