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Filtering by: Creator Zhang, Heng Remove constraint Creator: Zhang, Heng Academic Affiliation Electrical Engineering and Computer Science Remove constraint Academic Affiliation: Electrical Engineering and Computer Science

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  • Ocean electric energy extraction opportunities

    Creator:
    Zhang, Heng
    Abstract:
    The world's oceans contain tremendous renewable energy potentials. It is estimated that if 0.2% of the ocean's untapped energy could be harnessed, it could provide power sufficient for the entire world [1]. This thesis provides a comprehensive description of the state-of-the-art of ocean energy extraction technologies and lessons learned from...
    Resource Type:
    Masters Thesis
    Full Text:
    AN ABSTRACT OF THE THESIS OF Heng Zhang for

  • Applied color processing

    Creator:
    Zhang, Heng
    Abstract:
    The quality of a digital image pipeline relies greatly on its color reproduction which should at a minimum handle the color constancy, and the final judgment of the excellence of the pipeline is made through subjective observations by humans. This dissertation addresses a few topics surrounding the color processing of...
    Resource Type:
    Dissertation
    Full Text:
    THE DISSERTATION OF Heng Zhang for the degree of Doctor of Philosophy in Electrical and Computer

  • Painterly rendering using space-time varying style parameters

    Creator:
    Kagaya, Mizuki
    Abstract:
    Automatic painterly rendering systems have been proposed but they opted for selecting a single style to generate paintings from images, which lacks the ability of creatively using multiple styles to focus important objects and deemphasize unimportant part of the scenes. We provide a multi-style painting framework to address this issue...
    Resource Type:
    Masters Thesis
    Full Text:
    -Time Varying Style Parameters Abstract approved: Eugene Zhang Automatic painterly rendering systems

  • Interactive 3D line integral convolution on the GPU

    Creator:
    Lakshmanan, Vasumathi
    Abstract:
    The Line Integral Convolution (LIC) is a mainstay of flow visualization. It is, however, computationally intensive, which limits its interactivity. Also, when used to view three-dimensional (3D) vector fields, the resulting images are dense and cluttered, making it difficult to perceive the flow on the interior parts of the field....
    Resource Type:
    Masters Thesis
    Full Text:
    . I thank Dr. Ron Metoyer and Dr. Eugene Zhang, whose courses have helped me in gaining

  • Action Segmentation with Limited Supervision

    Creator:
    Li, Jun
    Abstract:
    In this dissertation, we address action segmentation in videos under limited supervision. The goal of action segmentation is to predict an action class for each frame of a video. The limited supervision means ground truth labels of video frames are not available in training. We focus on three types of...
    Resource Type:
    Dissertation
    Full Text:
    , Professor Fuxin Li, Professor Alan Fern and Professor Yue Zhang. I thank Professor Fuxin Li for his insight

  • Robust and Efficient Classification of Videos in the Wild

    Creator:
    Mahasseni, Behrooz
    Abstract:
    Recognizing human actions in videos is a long-standing problem in computer vision with a wide range of applications including video surveillance, content retrieval, and sports analysis. This thesis focuses on addressing efficiency and robustness of video classification in unconstrained real-world settings. The thesis work can be broadly divided into four...
    Resource Type:
    Dissertation

  • New Techniques for Multi-Channel Biosignal Acquisition and Low-Power, Low-Resistance-Measurement Systems

    Creator:
    Kim, Jinyong
    Abstract:
    Dense electrical recording of biosignals has been developed to provide spatial resolution and precise temporal information for health monitoring, diagnostics, and clinical research. However, more electrodes require more wires, and wiring density quickly becomes a limiting factor. To break this bottleneck, we proposed a frequency-division multiplexing (FDM) based architecture for...
    Resource Type:
    Dissertation

  • Learning with Limited Labeled Data in Natural Language Processing

    Creator:
    Obeidat, Rasha
    Abstract:
    The advent of deep learning models leads to a substantial improvement in a wide range of NLP tasks, achieving state-of-art performances without any hand-crafted features. However, training deep models requires a massive amount of labeled data. Labeling new data as a new task or domain emerges consumes time and efforts...
    Resource Type:
    Dissertation

  • Knowledge Base Completion Leveraging Natural Language Data

    Creator:
    Shahbazi, Hamed
    Abstract:
    Information about named entities (real-world objects) is usually harvested from different sources and organized as a multiple relational directed graph in Knowledge Bases (KBs). KBs play essential roles in many NLP modules including question answering, fact-checking, search engines, etc. KBs are big but still incomplete: relational information among entities is...
    Resource Type:
    Dissertation

  • Movement Pattern Detection Through IMU and Barometer

    Creator:
    Qian, Yang
    Abstract:
    Movement pattern detection can be applied in a variety of applications such as assisting independent living of seniors at home, behaviour understanding in surveillance systems, sports analytics, and robotics. This project develops a scheme that fuses information from different sensors to detect movement patterns. This report contains three main parts:...
    Resource Type:
    Capstone Project
    Full Text:
    Cybernetics, volume 7, pages 4220–4225 Vol. 7, Aug 2005. [3] Cai Guowei and Chen, Ben M andLee, Tong Heng