Journal of Integrative Bioinformatics (Aug 2022)

KaIDA: a modular tool for assisting image annotation in deep learning

  • Schilling Marcel P.,
  • Schmelzer Svenja,
  • Klinger Lukas,
  • Reischl Markus

DOI
https://doi.org/10.1515/jib-2022-0018
Journal volume & issue
Vol. 19, no. 4
pp. 128 – 44

Abstract

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Deep learning models achieve high-quality results in image processing. However, to robustly optimize parameters of deep neural networks, large annotated datasets are needed. Image annotation is often performed manually by experts without a comprehensive tool for assistance which is time- consuming, burdensome, and not intuitive. Using the here presented modular Karlsruhe Image Data Annotation (KaIDA) tool, for the first time assisted annotation in various image processing tasks is possible to support users during this process. It aims to simplify annotation, increase user efficiency, enhance annotation quality, and provide additional useful annotation-related functionalities. KaIDA is available open-source at https://git.scc.kit.edu/sc1357/kaida.

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