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Full-Text Articles in Training and Development
Garbage In ≠ Garbage Out: Exploring Gan Resilience To Image Training Set Degradations, Nicholas Crino, Bruce A. Cox, Nathan B. Gaw
Garbage In ≠ Garbage Out: Exploring Gan Resilience To Image Training Set Degradations, Nicholas Crino, Bruce A. Cox, Nathan B. Gaw
Faculty Publications
Generative Adversarial Networks (GANs) have received immense attention in recent years due to their ability to capture complex, high-dimensional data distributions without the need for extensive labeling. Since their conception in 2014, a wide array of GAN variants have been proposed featuring alternative architectures, optimizers, and loss functions with the goal of improving performance and training stability. This manuscript focuses on quantifying the resilience of a GAN architecture to specific modes of image degradation. We conduct systematic experimentation to empirically determine the effects of 10 fundamental image degradation modes, applied to the training image dataset, on the Fréchet inception distance …
Garbage In ≠ Garbage Out: Exploring Gan Resilience To Image Training Set Degradations, Nicholas M. Crino
Garbage In ≠ Garbage Out: Exploring Gan Resilience To Image Training Set Degradations, Nicholas M. Crino
Theses and Dissertations
Generative Adversarial Networks (GANs) have received increasing attention in recent years due to their ability to capture complex, high-dimensional data distributions without the need for extensive labeling. Since their conception in 2014, a wide array of GAN variants have been proposed featuring alternative architectures, optimizers, and loss functions with the goal of improving performance and training stability. While this research has yielded GAN variants robust to training set shrinkage and corruption, our research focuses on quantifying the resilience of a GAN architecture to specific modes of image degradation. We conduct systematic experimentation to determine empirically the effects of 10 fundamental …
The Application Of Virtual Reality In Firefighting Training, Dylan A. Gagnon
The Application Of Virtual Reality In Firefighting Training, Dylan A. Gagnon
Theses and Dissertations
Immersive simulations such as virtual reality is becoming more prevalent for use in training environments for many professions. United States Air Force firefighters may benefit from incorporating VR technology into their training program to increase organizational commitment, job satisfaction, self-efficacy, and job performance. With implementing a new training platform, it is also important to understand the relationship between these variables and the perceived benefits and efficacy of the VR training, which has not yet been studied in previous research. This study addresses this issue by gathering data from fire departments currently fielding a VR fire training platform.
The Effect Of Interactivity And Instructional Exposure On Learning Effectiveness And Knowledge Retention: A Comparative Study Of Two U.S. Air Force Computer-Based Training (Cbt) Courses For Network User Licensing, Matthew J. Imperial
Theses and Dissertations
The United States Air Force (USAF) currently employs the use of computer-based training (CET) across a host of requirements. One such requirement is in the Information Assurance (IA) arena and involves the training/licensing of over one-million computer network end-users. USAF use of CETs has been shown to possess a potential for substantial fiscal savings. However, studies investigating the learning outcomes of learning effectiveness (initial learning) and knowledge retention (sustained learning) associated with USAF CETs are lacking.