Automated plankton image recognition
Abstract: The presentation considers computer vision and machine learning in plankton image recognition, especially from a point of view of applications. Digital image processing and analysis with machine learning methods could enable efficient machine intelligence solutions for various areas of useful data-centric engineering applications. The goal of the research is to automate plankton image classification, instead of very laborious manual processing of a huge number of images. Challenges with imbalance of datasets, domain adaptation, active learning, open-set classification, metric learning of similarities, fine-grained recognition, and cross-modal learning are considered and related examples are given in plankton recognition, based on the AI-based research of LUT Computer Vision and Pattern Recognition Laboratory (CVPR Lab).
Speaker: Prof. Heikki Kälviäinen, Lappeenranta-Lahti University of Technology LUT, Finland
IGB Colloquia open up!
IGB strives to facilitate and accelerate the exchange of knowledge and ideas within and also outside of IGB. One element contributing to inter- and transdisciplinary exchange, and more (scientific) cooperation and innovation, is to open up IGB Colloquia to an interested external audience from science (other research institutes, universities, laboratories) as well as practice (i.e. conservationists, freshwater/land-use managers, authorities, associations). If you would like to join this IGB Colloquium as a guest, we ask you to register until the morning of the colloquium 10 o'clock the latest. After we have checked your registration, you will receive the participation link.
