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

Karlı, Berat Tuna
Şen, Deniz
Temizel, Alptekin
36th AAAI Conference on Artificial Intelligence, Adversarial Machine Learning and Beyond Workshop


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The performance of a supervised deep learning model is highly dependent on the quality and variety of the images in the training dataset. In some applications, it may be impossible to obtain more images. Data augmentation methods have been proven to be successful in increasing the performance of deep learning models with limited data. Recent improvements on Generative Adversarial Networks (GAN) algorithms and structures resulted in improved image quality and diversity and made GAN training possible with lim...
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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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Frequent Web navigation patterns generated by using Web usage mining techniques provide valuable information for several applications such as Web site restructuring and recommendation. In conventional Web usage mining, semantic information of the Web page content does not take part in the pattern generation process. In this work, we investigate the effect of semantic information on the patterns generated for Web usage mining in the form of frequent sequences. To this aim, we developed a technique and a fram...
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Flight simulator systems generally use a separate image-generator component. The host is responsible for the positional data updates of the entities and the image generator is responsible for the rendering process. In such systems, the sense of presence is decreased by model flickering. This study presents a method by which the host can minimize model flickering in the image-generator output. The method is based on preexisting algorithms, such as visibility culling and level of detail management of 3D model...
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: