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From ISLAB/CAISR
Investigating Robustness of DNNs
Keywords deep neural networks, robustness  +
Level Master  +
OneLineSummary This master thesis project aims at characterizing sensitivity to classification of images (based on deep neural networks).  +
Prerequisites Learning Systems, Data Mining, Parallel programming  +
References Szegedy, Christian, et al. "Intriguing proSzegedy, Christian, et al. "Intriguing properties of neural networks." arXiv preprint arXiv:1312.6199 (2013). Hinton, Geoffrey E., and Ruslan R. Salakhutdinov. "Reducing the dimensionality of data with neural networks." Science 313.5786 (2006): 504-507. Hinton, Geoffrey E. "Learning multiple layers of representation." Trends in cognitive sciences 11.10 (2007): 428-434. Nguyen, Anh, Jason Yosinski, and Jeff Clune. "Deep Neural Networks are Easily Fooled: High Confidence Predictions for Unrecognizable Images." arXiv preprint arXiv:1412.1897 (2014). Krizhevsky, Alex, Ilya Sutskever, and Geoffrey E. Hinton. "Imagenet classification with deep convolutional neural networks." Advances in neural information processing systems. 2012.ural information processing systems. 2012.
StudentProjectStatus Finished  +
Supervisors Jens Lundström + , Stefan Byttner +
ThesisAuthor Matej Uličný  +
TimeFrame Spring 2015  +
Title Investigating Robustness of DNNs  +
Categories StudentProject  +
Modification dateThis property is a special property in this wiki. 16 October 2016 10:16:11  +
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