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Physical Sciences and Mathematics Commons™
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Full-Text Articles in Physical Sciences and Mathematics
Adversarially Reweighted Sequence Anomaly Detection With Limited Log Data, Kevin Vulcano
Adversarially Reweighted Sequence Anomaly Detection With Limited Log Data, Kevin Vulcano
All Graduate Theses and Dissertations, Fall 2023 to Present
In the realm of safeguarding digital systems, the ability to detect anomalies in log sequences is paramount, with applications spanning cybersecurity, network surveillance, and financial transaction monitoring. This thesis presents AdvSVDD, a sophisticated deep learning model designed for sequence anomaly detection. Built upon the foundation of Deep Support Vector Data Description (Deep SVDD), AdvSVDD stands out by incorporating Adversarial Reweighted Learning (ARL) to enhance its performance, particularly when confronted with limited training data. By leveraging the Deep SVDD technique to map normal log sequences into a hypersphere and harnessing the amplification effects of Adversarial Reweighted Learning, AdvSVDD demonstrates remarkable efficacy …
A Classification Of Tensors In Ecsk Theory, Joshua James Leiter
A Classification Of Tensors In Ecsk Theory, Joshua James Leiter
All Graduate Theses and Dissertations, Spring 1920 to Summer 2023
You might have heard of Einstein’s theory of General relativity (GR): it is the one where mass and energy curve the fabric of spacetime to create gravity. This is the major theory which allows communication through satellites and our GPS to work too! Wormholes have interested me, but there are some issues about forming them in GR. Interestingly enough, elementary particles are also characterized by their spin in the standard model. However, intrinsic spin is nowhere geometrically coupled to the geometry of spacetime in Einstein’s theory. Later, Élie Cartan, Dennis Sciama, and Tom Kibble all flushed out adding different aspects …
Deep Learning With Attention Mechanisms In Breast Ultrasound Image Segmentation And Classification, Meng Xu
Deep Learning With Attention Mechanisms In Breast Ultrasound Image Segmentation And Classification, Meng Xu
All Graduate Theses and Dissertations, Spring 1920 to Summer 2023
Breast cancer is a great threat to women’s health. Breast ultrasound (BUS) imaging is commonly used in the early detection of breast cancer as a portable, valuable, and widely available diagnosis tool. Automated BUS image analysis can assist radiologists in making accurate and fast decisions. Generally, automated BUS image analysis includes BUS image segmentation and classification. BUS image segmentation automatically extracts tumor regions from a BUS image. BUS image classification automatically classifies breast tumors into benign or malignant categories. Multi-task learning accomplishes segmentation and classification simultaneously, which makes it more appealing and practical than an either individual task. Deep neural …