In this bachelor’s thesis I explore how convolutional neural networks for image classification tasks can be deployed to mobile devices for evaluation purposes. I focused on
models defined and trained with the popular TensorFlow-Slim library. The result of this
project is an Android app that allows you to deploy such models without making changes
to the source code. Moreover, I describe the differences between convolutional neural net-
works and regular neural networks with regards to a core task in the field of computer
vision, image classification. I then briefly outline the potential of transfer learning in the
context of image classification. Finally, I give a detailed description on the design goals,
development process and architecture of the app.
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In this bachelor’s thesis I explore how convolutional neural networks for image classification tasks can be deployed to mobile devices for evaluation purposes. I focused on
models defined and trained with the popular TensorFlow-Slim library. The result of this
project is an Android app that allows you to deploy such models without making changes
to the source code. Moreover, I describe the differences between convolutional neural net-
works and regular neural networks with regards to a core...
»