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Filtering by: Contributor Soldatov, Alexey I. Remove constraint Contributor: Soldatov, Alexey I. Academic Affiliation Electrical Engineering and Computer Science Remove constraint Academic Affiliation: Electrical Engineering and Computer Science

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  • Test case prioritization

    Creator:
    Malishevsky, Alexey Grigorievich
    Abstract:
    Regression testing is an expensive software engineering activity intended to provide confidence that modifications to a software system have not introduced faults. Test case prioritization techniques help to reduce regression testing cost by ordering test cases in a way that better achieves testing objectives. In this thesis, we are interested...
    Resource Type:
    Dissertation
    Full Text:
    AN ABSTRACT OF THE DISSERTATION OF Alexey Grigorievich

  • Pixel- and Frame-level Video Labeling using Spatial and Temporal Convolutional Networks

    Creator:
    Lei, Peng
    Abstract:
    This dissertation addresses the problem of video labeling at both the frame and pixel levels using deep learning. For pixel-level video labeling, we have studied two problems: i) Spatiotemporal video segmentation and ii) Boundary detection and boundary flow estimation. For the problem of spatiotemporal video segmentation, we have developed recurrent...
    Resource Type:
    Dissertation
    Full Text:
    using deep learning. For pixel-level video labeling, we have studied two problems: i) Spatiotemporal

  • Enabling Virtual Globes for A Visual-Auditory User Experience of Spatial Data

    Creator:
    Gune, Aditya N.
    Abstract:
    Geographical datasets are large, complex, and can be difficult for users to navigate and derive meaning from. These datasets, as well as the unique insights derived from them, provide tremendous opportunity for social change -- many of the global challenges humankind is currently facing can benefit from analytics or visualization...
    Resource Type:
    Masters Thesis
    Full Text:
    immersive and multimodal way that enhances the user’s cognition of the data. In this thesis, I investigate

  • Modeling spintronics devices in Verilog-A for use with industry-standard simulation tools

    Creator:
    Engelbrecht, Linda M.
    Abstract:
    As the semiconductor industry works to integrate increasingly more "non-CMOS" devices onto CMOS ICs, compact model development has become an important step in the circuit/system verification tool flow. This research focuses on the two- and three-dimensional modeling of the physical phenomena that occur in nanoscale magnetic devices. This includes the...
    Resource Type:
    Dissertation
    Full Text:
    -perpendicular-to-plane, spin transfer torque (STT) as stimulus. All device compact models have electrical I/O

  • Designing Diversity and Inclusion Processes and Tools for Sustainable Open Source

    Creator:
    Guizani, Mariam
    Abstract:
    Over time, Open Source Software (OSS) has become indispensable in the creation and upkeep of software products, serving as the fundamental building block for widely used solutions in our daily lives, including applications that enable communication, entertainment, and productivity. A sustainable OSS ecosystem is one that attracts and retains a...
    Resource Type:
    Dissertation
    Full Text:
    domains, Open Source itself is challenged in terms of the Diversity and Inclusion (D&I) of its community

  • Guided Translation of Algorithmic Notation into Functional Programs

    Creator:
    Fedorin, Danila
    Abstract:
    The use of board games for teaching introductory computer science is a promising recent avenue of research. The goal is to introduce computing concepts through their use in the implementations of simple games, thereby keeping students engaged through their learning process. However, there is a gap between students' algorithmic descriptions...
    Resource Type:
    Masters Thesis
    Full Text:
    -suited for immediate ex- ecution. In this thesis, I present a system aimed at helping students refine

  • Two Sides of a Coin: Adversarial-Based Image Privacy and Defending Against Adversarial Perturbations for Robust CNNs

    Creator:
    Rajabi, Arezoo
    Abstract:
    Emergence of highly accurate Convolutional Neural Networks (CNNs) with the capability to process large datasets, has led to their popularity in many applications, including safety/security-sensitive (e.g. disease recognition, self-driving cars). Despite the high accuracy of convolutional neural networks, they have been found to be susceptible to adversarial noise added to...
    Resource Type:
    Dissertation
    Full Text:
    cloud image storage setting. We propose and evaluate two adversarial-based protection methods: (i) a

  • Auxiliary Tasks for Efficient Learning of Point-Goal Navigation

    Creator:
    Desai, Saurabh Satish
    Abstract:
    Top-performing approaches to embodied AI tasks like point-goal navigation often rely on training agents via reinforcement learning over tens of millions (or even billions) of experiential steps – learning neural agents that map directly from visual observations to actions. In this work, we question whether these extreme training durations are...
    Resource Type:
    Masters Thesis
    Full Text:
    and Computer Science Dean of the Graduate School I understand that my thesis will become part of the

  • A Deep Action Segmentation and Its Explanation with a Dictionary of Meaningful Attention Maps

    Creator:
    Trigkakis, Dimitrios
    Abstract:
    This thesis addresses the problem of temporal action segmentation in videos, where the goal is to label every video frame with the appropriate action class present. We focus on the domain of NFL football videos, where action classes represent common football play types. For action segmentation, we use a temporal...
    Resource Type:
    Masters Thesis
    Full Text:
    the Graduate School I understand that my thesis will become part of the permanent collection of

  • Window Axial Vision Transformer for Image Classification

    Creator:
    Lee, Jisoo
    Abstract:
    Currently, a popular approach to image classification uses the deep Transformer architecture. In a Transformer, the attention mechanism enables the model to learn efficiently with fewer computational resources than the convolutional neural networks (CNNs). In this thesis, we study the sparse attention mechanism widely used in the Transformers developed specifically...
    Resource Type:
    Masters Thesis
    Full Text:
    Science Head of the School of Electrical Engineering and Computer Science Dean of the Graduate School I