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Data efficient methods for plankton image classification

Grant number: 22/09376-2
Support Opportunities:Scholarships in Brazil - Post-Doctoral
Effective date (Start): August 01, 2022
Effective date (End): October 31, 2023
Field of knowledge:Physical Sciences and Mathematics - Computer Science - Computing Methodologies and Techniques
Acordo de Cooperação: Belmont Forum
Principal Investigator:Nina Sumiko Tomita Hirata
Grantee:Alexandre Morimitsu
Host Institution: Instituto de Matemática e Estatística (IME). Universidade de São Paulo (USP). São Paulo , SP, Brazil
Associated research grant:18/24167-5 - World Wide Web of Plankton Image Curation (www.pic), AP.R

Abstract

The main objective of this postdoctoral project is to continue the development of machine learning based computational methods to accelerate both the annotation and classification of plankton images, minimizing the required effort from the expert. The method must be able to make effective use of previously generated knowledge, quickly producing new classifiers adapted to new images or usage conditions. Some of the topics to be explored in the project are unsupervised and semi-supervised machine learning approaches, possibly including user-interaction mechanisms, as well as techniques related to novelty detection and class imbalance treatment. (AU)

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