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Filtering by: Creator Li, Dan Remove constraint Creator: Li, Dan Academic Affiliation Electrical Engineering and Computer Science Remove constraint Academic Affiliation: Electrical Engineering and Computer Science

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  • Adaptive Wing Loss for Robust Face Alignment via Heatmap Regression

    Creator:
    Wang, Xinyao
    Abstract:
    Heatmap regression has became one of the mainstream approaches to localize facial landmarks. As Convolutional Neural Network (CNN) and Recurrent Neural Network (RNN) are becoming popular in solving computer vision tasks, extensive research has been done on these architectures. However, the loss function for heatmap regression is rarely studied. In...
    Resource Type:
    Masters Thesis
    Full Text:
    for Robust Face Alignment via Heatmap Regression Abstract approved: Fuxin Li Heatmap regression has

  • Deep Segmentation in Plant Phenomics

    Creator:
    Kaur, Damanpreet
    Abstract:
    The abilities of plant biologists to characterize the genetic basis of physiological traits are limited by their abilities to obtain quantitative data representing precise details of trait variation and mainly to collect this data on a high-throughput scale at low cost. Deep learning-based methods have demonstrated unprecedented potential to automate...
    Resource Type:
    Masters Thesis
    Full Text:
    Plant Phenomics Abstract approved: Fuxin Li The abilities of plant biologists to characterize the

  • Methods for Detection and Recovery of Out-of-Distribution Examples

    Creator:
    Ratzlaff, Neale J.
    Abstract:
    Deep neural networks currently comprise the backbone of many applications where safety is a critical concern, for example: autonomous driving and medical diagnostics. Unfortunately these systems currently fail to detect out-of-distribution (OOD) inputs and can be prone to making dangerous errors when exposed to them. In addition, these same systems...
    Resource Type:
    Masters Thesis
    Full Text:
    Detection and Recovery of Out-of-Distribution Examples Abstract approved: Fuxin Li Deep neural networks

  • Video Analysis : Techniques for Semi-Supervised Video Object Instance Segmentation and Tracking-by-Detection in the Wild

    Creator:
    Firl, Alrik K.
    Abstract:
    This thesis consists of two major components. The first part is concerned with video object instance segmentation (VOS), which is the task of assigning per-pixel labels perframe of a video sequence to indicate foreground object instance membership, given the first frame ground truth mask. VOS has myriad applications, from video...
    Resource Type:
    Masters Thesis
    Full Text:
    Abstract approved: Fuxin Li This thesis consists of two major components. The first part is concerned

  • Printed Nanocomposite Devices and Flexible Electronics for Humidity Sensing

    Creator:
    Ajithkumar, Amritha
    Abstract:
    The thesis focuses on the development of a novel printed resistive humidity sensor and integrated flexible electronics for an RFID-enabled humidity sensing platform. We explored a hybrid nanocomposite material for humidity sensing consisting of carbon nanomaterials, conductive polymer and cellulose polymer that undergoes resistance change in response to humidity change....
    Resource Type:
    Masters Thesis
    Full Text:
    : ______________________________________________________ Li-Jing Cheng The thesis focuses on the development of a novel printed resistive

  • Quantum dot plasmon coupling : Fundamental study and applications

    Creator:
    Kannegulla, Akash
    Abstract:
    The dissertation focuses on the engineering of light-matter interaction using plasmonic nanoparticles and metamaterials to achieve enhanced luminescence and based on which to improve the performance of biosensing and light-emitting technologies. We designed and fabricated a spectrum of nanostructures to exhibit particular dispersion relations capable of controlling the spontaneous emission...
    Resource Type:
    Dissertation
    Full Text:
    Abstract approved: ______________________________________________________ Li-Jing (Larry) Cheng

  • Leveraging Structures of the Data in Deep Learning

    Creator:
    Li, Xingyi
    Abstract:
    The performance of deep learning frameworks could be significantly improved through considering the particular underlying structures for each dataset. In this thesis, I summarize our three work about boosting the performance of deep learning models through leveraging structures of the data. In the first work, we theoretically justify that, for...
    Resource Type:
    Dissertation
    Full Text:
    AN ABSTRACT OF THE DISSERTATION OF Xingyi Li for the degree

  • Energy-Aware Gossip Techniques for Wireless Broadcasting

    Creator:
    Li, Tingzhi
    Abstract:
    The current state of research on gossip techniques for wireless broadcasting is very limited because past research efforts have mostly focused on using gossip techniques for multicast communication. On the other hand, those research efforts that have focused on using gossip techniques for wireless broadcast communications ignore energy efficiency and...
    Resource Type:
    Masters Thesis
    Full Text:
    AN ABSTRACT OF THE THESIS OF Tingzhi Li for the degree of

  • Predicting and Improving Throughput, Responsiveness and Battery Life of Computer Systems by Machine Learning

    Creator:
    Li, Yunfan
    Abstract:
    The Machine Learning (ML) algorithms are increasingly explored in varies of fields including designing and optimizing computer systems. Recent research, such as optimizing memory/cache prefetching by ML training or predicting traffic pattern in throughput processors, also exhibits a promising future of introducing ML into computer system design and optimization. Throughput...
    Resource Type:
    Dissertation
    Full Text:
    AN ABSTRACT OF THE DISSERTATION OF Yunfan Li for the

  • The Familiarity Hypothesis: Explaining the Behavior of Deep Learning Methods in Out-of-Distribution Detection

    Creator:
    Guyer, Alexander
    Abstract:
    Many object recognition applications require detecting and responding to objects drawn from a different distribution from that of the training data. This task is referred to as out-of-distribution (OOD) detection, and it is often formulated as an outlier detection problem wherein the probability distribution of the known data P(X) is...
    Resource Type:
    Masters Thesis