dl course 2019

the 2019 version of the dl course

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Many thanks for the fascinanting projects. Here are the links to some of them:

Links to projects 2018

  • “Dog Breed Identification” Melanie Hugentobler, Andreea Wyss und Yacine Mekesser

  • “Dog Breed Identification” Tom Schäfer, Hans Engeli, Marco Flatt

  • “Classifying Real Estate Ad Images with Convolutional Neural Networks CAS Machine Intelligence” Reto Camenzind, Lukas Stöcklin, Julia Sulc

  • “Deep Fruits” Frank Meier, Georgios Laios, and Giovanni Lopez see also on github meierfra/deep_fruits

  • “iMaterialist Challenge (Furniture)” Pascal Freudiger, Roger Hämmertli, Ben Koch und Stefanie Saurwein

  • “Humpback Whale Identification Challenge” Roger Schwyn, Christoph Hubmann and Hubert Keller

Links to projects 2019

  • “Music classification with Deep Learning” Andreas Fischer, Bernd Novotny und Tobias Schieferdecker

  • “Land cover classification: Squeezing the lemon with AutoML” Timo Grossenbacher

  • “Malaria Cell Images” Pascal Wenger, Vinzenz Frauchiger und Tobias Steinbach

  • “Classification with CelebA” Merola Davide, Pauli Christian

  • “Plant Seedlings Classification” Ana Cira Garita Solano, Anna Riedo

  • “Find the Polar Bear” Dominique Ueltschi, Isabelle Kluser

  • “Facial Keypoints Detection” Marius Wolfensberger, Céline Schlosser

  • “Cycle GAN” Fabio Santschi

  • “Duck classification with CNNs” Fredi Weideli, Patrick Graber

  • “Der letzte Führerscheinneuling ist schon geboren!” Andreas Palm, Reto Stucki

  • “The „Find Walter“ Problem” Timur Erdag, Bruno Frei, Sandra Mark und Aaron Venetz

  • “Natural Images” André Wethmar, Roberto Ringenberg und Jan Schüpbach

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