https://github.com/petarv-/deep-lossy-fun
Accompanying demos for my TCES talk on loss function engineering
https://github.com/petarv-/deep-lossy-fun
adversarial-inputs deep-neural-networks deepdream image-processing keras loss-functions neural-style vgg16
Last synced: 11 months ago
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Accompanying demos for my TCES talk on loss function engineering
- Host: GitHub
- URL: https://github.com/petarv-/deep-lossy-fun
- Owner: PetarV-
- License: mit
- Created: 2017-02-27T22:21:13.000Z (over 9 years ago)
- Default Branch: master
- Last Pushed: 2017-03-03T18:21:52.000Z (over 9 years ago)
- Last Synced: 2025-05-06T19:49:44.424Z (about 1 year ago)
- Topics: adversarial-inputs, deep-neural-networks, deepdream, image-processing, keras, loss-functions, neural-style, vgg16
- Language: Python
- Size: 9.68 MB
- Stars: 8
- Watchers: 3
- Forks: 2
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# deep-lossy-fun
Accompanying demos for my TCES talk on loss function engineering.
The slides may be found [here](http://www.cl.cam.ac.uk/~pv273/slides/LOSSlides.pdf).
## Contents
- `adversarial/` contains the adversarial examples demo files
- `style_transfer/` contains the neural style transfer demo files
- `deepdream/` contains the DeepDream demo files
## Requirements
- TensorFlow
- Keras
- SciPy
## License
MIT