Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
Results
Showing 1 to 20 of 52 for “"learning networks"”.
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Optimizing deep learning networks using multi-armed bandits
Deep learning has gained significant attention recently following their successful use for applications such as computer vision, speech recognition, and natural language processing. These deep learning models are based on very large neural networks, which can require a significant amount of memory …
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Detection of human face from sketches using deep learning networks
… specifically, the recent state of the art deep learning techniques to identify people based on their sketches for law and enforcement. The dataset is collected from Chinese database (CUHK student dataset) that includes both photos and their corresponding sketches. The sketches are drawn by …
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Digital Bridges: How Art Educators Build Professional Learning Networks on Twitter
… in the #K12ArtChat, as a form of professional learning. Grounded in social constructivist learning, connectivism, and informal learning, this study addressed how and why art educators use Twitter Chats for professional growth and the potential impact of participation on their teaching …
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Primary strategy learning networks: a local study of a national initiative
… of one such initiative – Primary Strategy Learning Networks (DfES, 2004a). The research focuses on a reliance on school networks as power bases for promoting a national standards agenda. It considers the impact of an imposed model of school collaboration on the fluid nature of networking. …
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Using content and process scaffolds for collaborative discourse in asynchronous learning networks
Discourse, a form of collaborative learning, is one of the most widely used methods of teaching and learning in the online environment. Particularly, in large courses, discourse needs to be 'structured' to be effective. Historically, technology-mediated learning (TML) research has been inconclusive …
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Collaborative examinations in asyncronous learning networks : field experiments on collaborative learning through online assessments
With the proliferation of computer networks and the emergence of virtual teams, learning and knowledge sharing in the online environment has become an increasingly important topic. Applying constructivism and collaborative learning theories to assessment, the collaborative online exam is designed …
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A Hermeneutic Phenomenological Study of School Administrators’ Participation in Personal Learning Networks and Privacy Issues
… networking tools to participate in personal learning networks (PLN) while managing privacy. As school administrators digitally collaborate with PLN colleagues, they must construct an online identity and develop and cultivate relationships. Additionally, to engage in a PLN one must decide how …
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A Formative Evaluation of Personal Learning Networks for Professional Development in the Architecture + Design Industry
… research is a formative evaluation of personal learning networks to determine their applicability for professional development in the architecture and design industry. The researcher seeks to find a catalyst toward discipline-wide realization of integrated design practices. This research …
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The effects of digital audio on social presence, motivation and perceived learning in asynchronous learning networks
… motivation was a stronger indicator of perceived learning and satisfaction than social presence. In particular, extrinsic motivation measured by perceived usefulness was the strongest indicator of perceived learning and satisfaction. Between the two digital audio formats, the narrated Microsoft …
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ScatterNet Hybrid Frameworks for Deep Learning
… non-linear modulus, and pooling operations. Deep learning networks ignore these geometric considerations and compute descriptors having suitable invariance and stability to geometric transformations using (end-to-end) learned multi-layered network filters. These deep learning networks in recent …
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Multimodal machine translation
… being made in machine translation through deep learning networks. But there is relatively lesser progress made in using images to catalyze the translation tasks. In this study, we explore various models to incorporate the image features in the machine translation models. We start with a …
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Automatic Classification and Segmentation of Patterned Martian Ground Using Deep Learning Techniques
… images. This thesis demonstrates the use of deep learning techniques in the classification of Martian polygonally patterned ground from HiRISE images. Three tasks are considered, a binary classification to identify images containing polygons, multiclass classification distinguishing different …
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Decoding STEM: The Impact of Science, Technology, Engineering, and Mathematics (STEM) Outreach Programming on English Language Learners
… pedagogies which place emphasis on textbook learning can be challenging for students, especially those who are learning English at the same time. This case study examines a cohort of English Language Learners (ELLs) selected from a larger longitudinal STEM study that aimed to investigate how …
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A radial basis function approach to pricing and hedging options incorporating transaction costs
… methods. A general class of methods known as learning networks has been making significant inroads in option pricing literature. This thesis will adopt McLoone's hybrid linear/nonlinear training algorithm in developing RBF network models for the purpose of pricing and hedging options. An …
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Evolutionary deep learning
… of algorithms in various active areas of machine learning research. Deep neural networks are exhibiting an explosion in the number of parameters that need to be trained, as well as the number of permutations of possible network architectures and hyper-parameters. There is little guidance on how to …
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POCS Augmented CycleGAN for MR Image Reconstruction
… optimization problems. By contrast, deep learning (DL)-based reconstruction methods do not need any explicit analytical data model and are robust to noise due to its large data-based training, which both make DL a versatile tool for fast and high-fidelity MR image reconstruction. While DL …
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Policy Advocacy - Advocating For Redesigned Adult Learning In Support of Value-Added Teacher Evaluation
<p>ABSTRACT </p> <p>Redesigning adult learning in order to move toward excellence in the classroom is critical to improving the state of the reform work occurring in our schools. Building coherence among teams of educators by linking staff development to student achievement is the goal of the …
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Social Intelligence for Cognitive Radios
… of developing decentralized, self-organizing networks that dynamically fit into their environment. In the course of accomplishing this, social language is defined as an efficient method for communicating coordination information among cognitive radios inspired by natural societies. This …
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Improving the Interpretation of Magnetic Tensor Data Using Deep Learning
… magnetic data. I examined ways in which machine learning techniques can be applied to magnetic tensor data to automatically locate possible kimberlite targets and a method to sharpen smoothness based inversion models to provide a clearer image of the subsurface. While machine learning networks …
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Visualizing and interpreting convolutional neural networks on genomic data
Deep learning's capability to learn derived features through a hierarchy of non-linear layers has proven superior to other machine learning methods. However, interpretation of the resulting genomic deep learning networks remains challenging. While many network visualization tools focus on directly …
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