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Building of a binary machine learning classifier for radiographic images using the Google Seedbank platform
Potential applications for predictive models providing a binary classification based on radiographic images are manifold. A modular machine learning application that can be trained with different radiographic data sets without any programming skills would, therefore, be desirable.
The project shall be using Googles Seedbank platform:
https://research.google.com/seedbank/seed/cat_vs_dog_part_one
The project shall be using Googles Seedbank platform: https://research.google.com/seedbank/seed/cat_vs_dog_part_one
To set up a binary machine learning classifier for radiographic images using the Google Seedbank platform, which can be used for different imaging datasets.
To set up a binary machine learning classifier for radiographic images using the Google Seedbank platform, which can be used for different imaging datasets.
Dr. med. Patrick Eppenberger, Dipl. Industrial Designer FH
Leader of Paleopathology and Mummy Studies Group a.i.
Institute of Evolutionary Medicine (IEM)
University of Zurich
Winterthurerstrasse 190
CH-8057 Zurich, Switzerland
Office: Room Y42 G86a
Phone +41 44 635 05 43, Mobile +41 79 4876574, Fax: +41 44 635 05 19
Dr. med. Patrick Eppenberger, Dipl. Industrial Designer FH Leader of Paleopathology and Mummy Studies Group a.i. Institute of Evolutionary Medicine (IEM) University of Zurich Winterthurerstrasse 190 CH-8057 Zurich, Switzerland Office: Room Y42 G86a Phone +41 44 635 05 43, Mobile +41 79 4876574, Fax: +41 44 635 05 19