Dr. Pol del Aguila Pla presented “Remote and interactive image processing programming laboratories with Jupyter” during a webinar at the IEEE Finland joint chapter of the Signal Processing Society (SPS) and Circuits and Systems Society (CAS), chaired by Assistant Professor Alexander Jung from Aalto University.

University computer laboratories as we knew them are dead. The widespread availability of networked computing resources among students (smartphones, tablets, and laptops), combined with the existence of enabling technologies like Jupyter, can no longer be ignored when allocating resources for higher education in STEM.”, said Pol del Aguila Pla.

Work on the project started in the months before the pandemic unraveled and effectively rendered the traditional format impossible. Since then, the team in the Biomedical Imaging Group at EPFL  has been simultaneously developing and running the graded laboratory sessions for their popular basic and advanced image-processing (IP) courses (up to 280 students) as online experiences on an institute-wide JupyterLab instance (Noto at EPFL). The students become experts in the implementation and application of concepts like image wavelet transforms, morphological operators, interpolation, and neural networks for pixel classifications, and do so working at their own pace and anytime. This has resulted in excellent feedback from students and teaching assistants alike.

In the presentation at the IEEE vTools event in June, Dr. Pol del Aguila Pla outlined the pedagogical goals, technical work and results of this project. He covered

  • the development of a grading library for image and signal processing exercises with plagiarism detection (relying on the nbgrader framework),
  • the development of an interactive image viewer for Jupyter Notebooks (harnessing ipywidgets and Matplotlib),
  • the development of a dedicated image processing JavaScript library to enable care-free realistic pixel-by-pixel IP algorithm programming, and
  • the use of polyglot notebooks (JavaScript + Python, harnessing the SoS framework), and,

as well as the analysis of the student feedback to date.

Watch the webinar here.

Dr. Pol del Aguila Pla is a research staff scientist at the CIBM SP EPFL Mathematical Imaging Section and a postdoctoral researcher in the Biomedical Imaging Group at EPFL, both headed by Prof. Michael Unser.

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