34C3 - Deep Learning Blindspots
https://media.ccc.de/v/34c3-8860-deep_learning_blindspots
Tools for Fooling the "Black Box"
In the past decade, machine learning researchers and theorists have created deep learning architectures which seem to learn complex topics with little intervention. Newer research in adversarial learning questions just how much “learning" these networks are doing. Several theories have arisen regarding neural network “blind spots” which can be exploited to fool the network. For example, by changing a series of pixels which are imperceptible to the human eye, you can render an image recognition model useless. This talk will review the current state of adversarial learning research and showcase some open-source tools to trick the "black box."
Katharine Jarmul
https://fahrplan.events.ccc.de/congress/2017/Fahrplan/events/8860.html
Видео 34C3 - Deep Learning Blindspots канала media.ccc.de
Tools for Fooling the "Black Box"
In the past decade, machine learning researchers and theorists have created deep learning architectures which seem to learn complex topics with little intervention. Newer research in adversarial learning questions just how much “learning" these networks are doing. Several theories have arisen regarding neural network “blind spots” which can be exploited to fool the network. For example, by changing a series of pixels which are imperceptible to the human eye, you can render an image recognition model useless. This talk will review the current state of adversarial learning research and showcase some open-source tools to trick the "black box."
Katharine Jarmul
https://fahrplan.events.ccc.de/congress/2017/Fahrplan/events/8860.html
Видео 34C3 - Deep Learning Blindspots канала media.ccc.de
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