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DTSTART:20210328T030000
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DTSTAMP:20210609T191452Z
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DTSTART;TZID=Europe/Zurich:20210630T180000
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DESCRIPTION:University computer laboratories as we knew them are dead. The 
 widespread availability of networked computing resources among students (s
 martphones\, tablets\, and laptops)\, combined with the existence of enabl
 ing technologies like Jupyter\, can no longer be ignored when allocating r
 esources for higher education in STEM.\n\nFor us at the EPFL's Biomedical 
 Imaging Group (Prof. Michael Unser)\, this realization sinked in just mont
 hs before the pandemic unraveled and effectively rendered the traditional 
 format impossible. Since then\, we have been simultaneously developing and
  running the graded laboratory sessions for our 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 beco
 me experts in the implementation and application of concepts like image wa
 velet transforms\, morphological operators\, interpolation\, and neural ne
 tworks for pixel classifications\, and do so working at their own pace and
  anytime. This has resulted in excellent feedback from students and teachi
 ng assistants alike.\n\nIn this presentation\, I will outline the pedagogi
 cal goals\, technical work and results of this project. Among others\, thi
 s will cover the development of polyglot notebooks (JavaScript + Python\, 
 harnessing the SoS framework) and a dedicated image processing JavaScript 
 library to enable care-free realistic pixel-by-pixel IP algorithm developm
 ent\, the design of an interactive image viewer for Jupyter Notebooks (har
 nessing ipywidgets and Matplotlib)\, the development of a grading library 
 for image and signal processing exercises with plagiarism detection (relyi
 ng on the nbgrader framework)\, and our analysis of the student feedback t
 o date.\n\nSpeaker(s): Dr. del Aguila Pla \, \n\nVirtual: https://events.v
 tools.ieee.org/m/274436
LOCATION:Virtual: https://events.vtools.ieee.org/m/274436
ORGANIZER:alex.jung@aalto.fi
SEQUENCE:0
SUMMARY:Remote and Interactive Image Processing Programming Laboratories wi
 th Jupyter
URL;VALUE=URI:https://events.vtools.ieee.org/m/274436
X-ALT-DESC:Description: <br /><p>University computer laboratories as we kne
 w them are dead. The widespread availability of networked computing resour
 ces among students (smartphones\, tablets\, and laptops)\, combined with t
 he existence of enabling technologies like Jupyter\, can no longer be igno
 red when allocating resources for higher education in STEM.</p>\n<p>&nbsp\
 ;</p>\n<p>For us at the EPFL's Biomedical Imaging Group (Prof. Michael Uns
 er)\, this realization sinked in just months before the pandemic unraveled
  and effectively rendered the traditional format impossible. Since then\, 
 we have been simultaneously developing and running the graded laboratory s
 essions for our 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 e
 xcellent feedback from students and teaching assistants alike.</p>\n<p>&nb
 sp\;</p>\n<p>In this presentation\, I will outline the pedagogical goals\,
  technical work and results of this project. Among others\, this will cove
 r the development of polyglot notebooks (JavaScript + Python\, harnessing 
 the SoS framework) and a dedicated image processing JavaScript library to 
 enable care-free realistic pixel-by-pixel IP algorithm development\, the d
 esign of an interactive image viewer for Jupyter Notebooks (harnessing ipy
 widgets and Matplotlib)\, the development of a grading library for image a
 nd signal processing exercises with plagiarism detection (relying on the n
 bgrader framework)\, and our analysis of the student feedback to date.</p>
END:VEVENT
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