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  • The automated inference of tree system

    Creator:
    Levine, Barry Arthur
    Abstract:
    Tree systems are used in syntactic pattern recognition for describing two-dimensional patterns. We extend results on tree automata with the introduction of the subtree-invariant equivalence relation R. R relates two trees when the appearance of one implies the appearance of the other in similar trees. A new state minimizing algorithm...
    Resource Type:
    Dissertation
    Full Text:
    privacy Professor Curtis R. Cook Tree systems are used in syntactic pattern recognition for describing

  • Special associative preprocessing structures for qualitative feature extraction

    Creator:
    Bibby, Michael C.
    Abstract:
    Existing pattern recognition and classification algorithms in computer vision require vast amounts of computations on input data. As a result, memory access time is a critical parameter in system performance. Tremendous parallelism in structure and algorithm is required for the system to operate in real-time. A preprocessing structure for qualitative...
    Resource Type:
    Masters Thesis
    Full Text:
    . Michael Powers Existing pattern recognition and classification algorithms in computer vision require

  • A statistical inference framework for finding recurring patterns in large data with applications to energy management

    Creator:
    You, Zeyu
    Abstract:
    We consider the problem of finding unknown patterns that are recurring across multiple sets. For example, finding multiple objects that are present in multiple images or a short DNA code that is repeated across multiple DNA sequences. We first consider a simple problem of finding a single unknown pattern in...
    Resource Type:
    Masters Thesis
    Full Text:
    . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 3 Single Pattern Recognition 13 3.1 Model

  • From multitarget tracking to event recognition in videos

    Creator:
    Brendel, William
    Abstract:
    This dissertation addresses two fundamental problems in computer vision—namely, multitarget tracking and event recognition in videos. These problems are challenging because uncertainty may arise from a host of sources, including motion blur, occlusions, and dynamic cluttered backgrounds. We show that these challenges can be successfully addressed by using a multiscale,...
    Resource Type:
    Dissertation
    Full Text:
    Tracking to Event Recognition in Videos Abstract approved: Sinisa Todorovic This dissertation addresses

  • The architecture and design of a neural network classifier

    Creator:
    Jiang, Jin
    Abstract:
    The objective of this thesis is to present the architecture and design of a neural network-based pattern classifier. The classifier detects textual characters which have been translated, rotated, and corrupted by noise. This form of pattern classifier differs significantly from traditional pattern classifiers. The neural network architecture used in implementing...
    Resource Type:
    Masters Thesis
    Full Text:
    Patterns 34 3.3 Structure of Pattern Recognition System 35 3.4 Input Data Grid 37 3.5 Comparison of

  • Don't Fool Me : Detecting Adversarial Examples in Deep Networks

    Creator:
    Li, Xin
    Abstract:
    Deep learning has greatly improved visual recognition in recent years. However, recent research has shown that there exist many adversarial examples that can negatively impact the performance of such an architecture. Different from previous perspectives that focus on improving the classifiers to detect the adversarial examples, this work focuses on...
    Resource Type:
    Masters Thesis
    Full Text:
    greatly improved visual recognition in recent years. How- ever, recent research has shown that there

  • Leaf shape recognition via support vector machines with edit distance kernels

    Creator:
    Sinha, Shriprakash
    Abstract:
    Edit distances are a well-established technique for classification problems. They have been employed successfully in many classification problems including chromosome classification and hand-written digit recognition. Virtually all machine learning algorithms represent the objects to be classified as vectors of features. However, edit distances provide only a measure of the difference...
    Resource Type:
    Masters Thesis

  • Image features and learning algorithms for biological, generic and social object recognition

    Creator:
    Zhang, Wei
    Abstract:
    Automated recognition of object categories in images is a critical step for many real-world computer vision applications. Interest region detectors and region descriptors have been widely employed to tackle the variability of objects in pose, scale, lighting, texture, color, and so on. Different types of object recognition problems usually require...
    Resource Type:
    Dissertation
    Full Text:
    final part of the dissertation describes a socially-driven clothes recognition system for an

  • Simultaneous segmentation and classification of bird song using CNN

    Creator:
    Narasimhan, Revathy
    Abstract:
    In bioacoustics, automatic animal voice detection and recognition from audio recordings is an emerging topic for animal preservation. Our research focuses on bird bioacoustics, where the goal is to segment bird syllables from the recording and predict the bird species for the syllables. Traditional methods for this task addresses the...
    Resource Type:
    Masters Thesis
    Full Text:
    FIGURES Figure Page 1.1 Stages of a bioacoustic species recognition system. . . . . . . . . . . . . . 2

  • Pattern discovery in noisy images

    Creator:
    Dhamodaran, Sharath Kumar
    Abstract:
    The Focused Ion Beam (FIB) tool is a versatile instrument for nano-machining in circuit editing. Circuit editing is one of the most important steps in the design of an electronic circuit on a chip. Circuit editing can be improved by imaging of silicon plates and analyzing the resultant images. However...
    Resource Type:
    Masters Thesis