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Filtering by: Creator Remcho, Vincent T. Remove constraint Creator: Remcho, Vincent T. Degree Field Computer Science Remove constraint Degree Field: Computer Science Degree Level Doctoral Remove constraint Degree Level: Doctoral

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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 OF THE DISSERTATION OF William T. Langford for the degree of Doctor of Philosophy in Computer

  • The Evolution of Software Entropy in Open Source projects: An Empirical Study

    Creator:
    Mannan, Umme Ayda
    Abstract:
    Software entropy impacts the overall quality of software systems. High entropy hinders developers from understanding the purpose of a piece of code and can cause developers to make sub-optimal changes and introduce bugs. Researchers have used entropy scores to measure the naturalness of code. However, thus far, no one has...
    Resource Type:
    Technical Report
    Full Text:
    Engineering, 2009. ICSE 2009. IEEE 31st International Conference on. IEEE, 78–88. [15] Vincent J Hellendoorn

  • 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
    Full Text:
    Classes Latent Multitask Learning new video max y,v,h wTyvU TΦ(x, y,h) {{wv,y}, U} {ŷ, v̂} output

  • 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:
    activities. These spatiotemporal subvolumes are also referred to as 2D+t tracks, or tubes. We consider real

  • Fine-Grained Object Recognition Under Limited Training Data

    Creator:
    Lam, Michael Q.
    Abstract:
    This dissertation addresses object recognition in challenging settings, where distinct object classes are visually very similar (e.g., species of birds and insects) and/or access to training examples of object classes is limited (e.g., due to the associated high costs of data annotation). In this dissertation, we present a variety of...
    Resource Type:
    Dissertation
    Full Text:
    : for each training example (x,y∗) ∈D do 6: s0 = I(x) // initial search state 7: for each search step t

  • 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:
    from down- scaled clean images and original HR images (Sim(I, hrk(T (I)))), (ii) the generated high

  • New Directions in Search-based Structured Prediction: Multi-Task Learning and Integration of Deep Models

    Creator:
    Ma, Chao
    Abstract:
    This thesis studies the problem of structured prediction (SP), where the agent needs to predict a structured output for a given structured input (e.g., Part-of-Speech tagging sequence for an input sentence). Many important applications including machine translation in natural language processing (NLP) and image interpretation in computer vision can be...
    Resource Type:
    Dissertation
    Full Text:
    . Without loss of generality, we assume that each structured output y ∈ Y is represented using T discrete

  • Approximation Schemes in Planar Graphs

    Creator:
    Zheng, Baigong
    Abstract:
    There are growing interests in designing polynomial-time approximation schemes (PTAS) for optimization problems in planar graphs. Many NP-hard problems are shown to admit PTAS in planar graphs in the last decade, including Steiner tree, Steiner forest, two- edge-connected subgraphs and so on. We follow this research line and study several...
    Resource Type:
    Dissertation
    Full Text:
    (T ). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39 2.5 Examples for Lemma 2.30

  • Interpretable Machine Learning: Applications in Biology and Genomics

    Creator:
    Danaee, Padideh
    Abstract:
    Machine learning (ML) and deep learning (DL) models impact our daily lives with applications in natural language modeling, image analysis, healthcare, genomics, and bioinformatics. The exponential growth of biological sequence data necessitates accompanying advances in computational methods. Although deep learning is highly effective for detecting and classifying biological sequences, challenges...
    Resource Type:
    Dissertation
    Full Text:
    distribution. . . . . . . . . . . . . . . . . . . . . . . 55 5.2 t-SNE plots are visualizing gene expression

  • Understanding Software-2.0: A Study of Machine Learning library usage and evolution

    Creator:
    Dilhara, Malinda, Ketkar, Ameya, and Dig, Danny
    Abstract:
    Enabled by a rich ecosystem of Machine Learning (ML) libraries, programming using learned models, i.e., Software-2.0, has gained substantial adoption. However, we do not know what challenges developers encounter when they use ML libraries. With this knowledge gap, researchers miss opportunities to contribute to new research directions, tool builders do...
    Resource Type:
    Research Paper