Improving Perceptual Quality of Adversarial Images Using Perceptual Distance Minimization and Normalized Variance Weighting

Date

2022-02-28

Author

Karlı, Berat Tuna
Şen, Deniz
Temizel, Alptekin

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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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https://hdl.handle.net/11511/97506

Conference Name

36th AAAI Conference on Artificial Intelligence, Adversarial Machine Learning and Beyond Workshop

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Graduate School of Informatics, Conference / Seminar

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Improving operational performance of antennas on complex platforms by arranging their placements Bayseferoğulları, Can; Dural Ünver, Mevlüde Gülbin; Department of Electrical and Electronics Engineering (2010) The aim of this thesis is to improve the operational performance of the communication antennas mounted on complex platforms such as aircrafts and warships by arranging placements of these antennas. Towards this aim, primarily, in order to gain insight on the influence of geometrically simple structures composing the platform on antenna performance, a quarter wavelength monopole antenna placed at the center of a finite square ground plane is studied by using uniform Geometrical Theory of Diffraction (GTD). B...
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Citation Formats

B. T. Karlı, D. Şen, and A. Temizel, “Improving Perceptual Quality of Adversarial Images Using Perceptual Distance Minimization and Normalized Variance Weighting,” presented at the 36th AAAI Conference on Artificial Intelligence, Adversarial Machine Learning and Beyond Workshop, Vancouver, Kanada, 2022, Accessed: 00, 2022. [Online]. Available: https://hdl.handle.net/11511/97506.