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Filtering by: Creator Spies, Thomas A. Remove constraint Creator: Spies, Thomas A. Degree Field Computer Science Remove constraint Degree Field: Computer Science

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  • Evaluation functions in aerial image segmentation

    Creator:
    Langford, William T.
    Abstract:
    Remote sensing is the most practical way to acquire large amounts of land cover data for monitoring and understanding environmental change, so it is important to be able to map land cover from imagery. Maps defining land cover patches as polygons rather than pixels greatly improve processing efficiency in models...
    Resource Type:
    Dissertation
    Full Text:
    Abstract approved: Thomas G. Dietterich Warren Cohen Remote sensing is the most practical way to acquire

  • A specialized ATMS for equivalence relations

    Creator:
    Koff, Caroline Nan
    Abstract:
    A specialized ATMS for efficiently computing equivalence relations in multiple contexts is introduced. This specialized ATMS overcomes the problems with existing solutions to reasoning with equivalence relations. The most direct implementation of an equivalence relation in the ATMS-encoding the reflexive, transitive, and symmetric rules in the consumer architecture-produces redundant equality...
    Resource Type:
    Masters Thesis
    Full Text:
    for privacy Thomas G. Dietterich. A specialized ATMS for efficiently computing equivalence relations

  • A laboratory station timetable problem

    Creator:
    Mickelsen, Thomas E.
    Abstract:
    The general problem of classroom scheduling is well known to be NP-complete. A typical classroom scheduling problem is that of assigning students to a limited number of pieces of laboratory equipment. Frequently several identical pieces of equipment are available only at fixed hours and have limited access due to physical...
    Resource Type:
    Capstone Project
    Full Text:
    ) A Laboratory Station Timetable Problem Thomas E

  • A study of distance-based machine learning algorithms

    Creator:
    Wettschereck, Dietrich
    Abstract:
    Distance-based algorithms are machine learning algorithms that classify queries by computing distances between these queries and a number of internally stored exemplars. Exemplars that are closest to the query have the largest in uence on the classi cation assigned to the query. Two speci c distance-based algorithms, the nearest neighbor...
    Resource Type:
    Dissertation
    Full Text:
    the degree of Doctor of Philosophy in Computer Science presented on June 7, 1994. Title: A Study of

  • Correct abstraction in counter-planning : a knowledge compilation approach

    Creator:
    Flann, Nicholas S.
    Abstract:
    Knowledge compilation improves search-intensive problem-solvers that are easily specified but inefficient. One promising approach improves efficiency by constructing a database of problem-instance/best-action pairs that replace problem-solving search with efficient lookup. The database is constructed by reverse enumeration- expanding the complete search space backwards, from the terminal problem instances. This approach...
    Resource Type:
    Dissertation
    Full Text:
    Correct abstraction in counter-planning : a knowledge

  • A Benchmarking Study of Unsupervised Anomaly Detection Algorithms

    Creator:
    Emmott, Andrew F.
    Abstract:
    It is common practice in the unsupervised anomaly detection literature to create experimental benchmarks by sampling from existing supervised learning datasets. We seek to improve this practice by identifying four dimensions important to real-world anomaly detection applications --- point difficulty, clusteredness of anomalies, relevance of features, and relative frequency of...
    Resource Type:
    Masters Thesis
    Full Text:
    degree of Master of Science in Computer Science presented on June 18, 2020. Title: A Benchmarking Study

  • A probabilistic model for anomaly detection in remote sensor streams

    Creator:
    Dereszynski, Ethan W.
    Abstract:
    Remote sensors are becoming the standard for observing and recording ecological data in the field. Such sensors can record data at fine temporal resolutions, and they can operate under extreme conditions prohibitive to human access. Unfortunately, sensor data streams exhibit many kinds of errors ranging from corrupt communications to partial...
    Resource Type:
    Masters Thesis
    Full Text:
    Computer Science presented on October 25th, 2007. Title: A Probabilistic Model for Anomaly Detection in

  • Converting English text to speech : a machine learning approach

    Creator:
    Bakiri, Ghulum
    Abstract:
    The task of mapping spelled English words into strings of phonemes and stresses ("reading aloud") has many practical applications. Several commercial systems perform this task by applying a knowledge base of expert-supplied letter-to-sound rules. This dissertation presents a set of machine learning methods for automatically constructing letter-to-sound rules by analyzing...
    Resource Type:
    Dissertation

  • A study of methods for fine-grained object classification of arthropod specimens

    Creator:
    Lin, Junyuan
    Abstract:
    Object categorization is one of the fundamental topics in computer vision research. Most current work in object categorization aims to discriminate among generic object classes with gross differences. However, many applications require much finer distinctions. This thesis focuses on the design, evaluation and analysis of learning algorithms for fine- grained...
    Resource Type:
    Masters Thesis
    Full Text:
    Master of Science in Computer Science presented on February 18, 2013. Title: A Study of Methods for

  • Classification context in a machine learning approach to predicting protein secondary structure

    Creator:
    Langford, Bill T.
    Abstract:
    An important problem in molecular biology is to predict the secondary structure of proteins from their primary structure. The primary structure of a protein is the sequence of amino acid residues. The secondary structure is an abstract description of the shape of the folded protein, with regions identified as alpha...
    Resource Type:
    Masters Thesis
    Full Text:
    Classification context in a machine learning approach to