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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 …
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 …
Data-Driven Recommendation Of Academic Options Based On Personality Traits, Aashish Ghimire
Data-Driven Recommendation Of Academic Options Based On Personality Traits, Aashish Ghimire
All Graduate Theses and Dissertations, Spring 1920 to Summer 2023
The choice of academic major and, subsequently, an academic institution has a massive effect on a person’s career. It not only determines their career path but their earning potential, professional happiness, etc. [1] About 40% of people who are admitted to a college do not graduate within six years. Yet, very limited resources are available for students to help make those decisions, and each guidance counselor is responsible for roughly 400 to 900 students across the United States. A tool to help these decisions would benefit students, parents, and guidance counselors.
Various research studies have shown that personality traits affect …
Development And Identification Of Metrics To Predict The Impact Of Dimension Reduction Techniques On Classical Machine Learning Algorithms For Still Highway Images, Wasim Akram Khan
All Graduate Theses and Dissertations, Spring 1920 to Summer 2023
We are witnessing an influx of data - images, texts, video, etc. Their high dimensionality and large volume make it challenging to apply machine learning to obtain actionable insight. This thesis explores several aspects pertaining to dimensional reduction: dimension reduction methods, metrics to measure distortion, image preprocessing, etc. Faster training and inference time on reduced data and smaller models which can be deployed on commodity hardware are a critical advantage of dimension reduction. For this study, classical machine learning methods were explored owing to their solid mathematical foundation and interpretability.
The dataset used is a time series of images from …
Composite Feature-Based Face Detection Using Skin Color Modeling And Svm Classification, Swathi Rajashekar
Composite Feature-Based Face Detection Using Skin Color Modeling And Svm Classification, Swathi Rajashekar
All Graduate Plan B and other Reports, Spring 1920 to Spring 2023
This report proposes a face detection algorithm based on skin color modeling and support vector machine (SVM) classification. Said classification is based on various face features used to detect specific faces in an input color image. A YCbCr color space is used to filter the skin color pixels from the input color image. Template matching is used on the result with various window sizes of the template created from an ORL face database. The candidates obtained above, are then classified by SVM classifiers using the histogram of oriented gradients, eigen features, edge ratio, and edge statistics features.