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Machine Learning in the Wild. Exploring new Applications using Deep Neural Networks

Machine Learning in the Wild. Exploring new Applications using Deep Neural Networks
Typ:Bachelor-/ Masterarbeit
Datum:offen (zu vergeben)
Betreuer:

M. Eng. Gabriela Molinar
M. Sc. Simon Stock
M. Sc. Marco Stang
M. Sc. Daniel Grimm

Machine Learning in the Wild. Exploring new Applications using Deep Neural Networks

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Background

AI has advanced over the last decade tremendously. Applications range from the detection of cats in YouTube videos (2012) to more serious research as skin cancer classification [1].
“Deep learning allows computational models that are composed of multiple processing layers to learn representations of data with multiple levels of abstraction.” [2] Therefore a vast range of possibilities for the use of deep learning is present and should be explored.
You will be supervised by one or more of four PhD-Candidates actively working with Machine Learning technologies at ITIV. Possible project subjects will be discussed in person. Own project ideas are also welcome! 

 

Tasks

  • Data Acquisition/Preprocessing
  • Network Architecture Design
  • Network Training
  • Creation of Prototypes/Sample Applications 

 

Required skills

  • Highly Motivated
  • Ambition to tackle difficult problems
  • Experience in Machine Learning and/or Programming is a plus

 

 

 

[1] A. Esteva et al. “Dermatologist-level classification of skin cancer with deep neural networks”, Nature, vol. 542, pp. 115-118, 2017.
[2] Y. Lecun, Y. Bengio, and G. Hinton, “Deep learning”, Nature, vol. 521, no. 7553, pp. 436–444, 2015.