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.
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Showing 1 to 20 of 63 for “"Neural networks (Computer science)"”.
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Evolved neural network approximation of discontinuous vector fields in unit quaternion space (S3) for anatomical joint constraint
… work briefly explores Support Vector Machine neural networks as joint configuration classifiers that group joint configurations into invalid and valid. A far more detailed investigation is carried out into the use of topologically evolved feed forward neural networks for the generation of …
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Knowledge-based artificial neural network modeling assessment: integrating heterogeneous genomics data to uncover lifespan regulation
… to grow. More specifically, genetic modeling and neural network building are gaining interest as it becomes a fundamental piece of most model building we see today. We propose a Knowledge-Based Artificial Neural Network (KBANN) to predict phenotype while providing insight to effected subsystems. …
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Applying generative adversarial networks to intelligent subsurface imaging and identification
… realistic GPR data using Generative Adversarial Networks. An innovative GAN ar- chitecture is proposed for generating GPR B-scans, which is, to the author’s knowledge, the first successful application of GAN to GPR B-scans. As one of the major contri- butions, a novel loss function is formulated …
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Classifying GPR images using convolutional neural networks
… four different architectures of convolutional neural networks. Two CNNs were newly proposed for this study, while the other two were used by other authors. These CNNs were trained using a couple of adjusted training options including initial learning rate, learn rate drop factor, and learn rate …
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Neural networks approach to process control : the case of processes with long dead times
Thesis submitted in compliance with the requirements for the Doctor's Degree in Technology: Electrical Engineering, Technikon Natal, Durban, South Africa, 1999.
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A unified algebraic framework extending from a 6-set discrete probability algebra and its application in deep learning
… can be used to delve into the neuron-level deep neural network structure and aims at improving the transparency of how the black box works and making advancements in detailed applications. Our approach extends a 6-Set Discrete Probability Algebra to a more systematic quantitative framework that …
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A comparative study of the performance of machine learning methods and deep neural networks in intrusion detection
Intrusion detection systems (IDS) can be improved by using machine learning to teach the IDS what traffic is normal and therefore should be allowed into a network, or what traffic is abnormal and should be denied access to a network. The performance of intrusion detection systems can be improved …
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Extensive Huffman-tree-based neural network for the imbalanced dataset and its application in accent recognition
… this thesis proposed an Extensive Huffman-Tree Neural Network (EHTNN), which fabricates multiple component neural network-enabled classifiers (e.g., CNN or SVM) using an extensive Huffman tree. Any given node in EHTNN can have arbitrary number of children. Compared with the Binary Huffman-Tree …
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An evaluation of the robustness of the natural-adversarial mutual information-based defense and malware classification against adversarial attacks for deep learning
… Recently researchers have shown that even deep neural networks (DNNs) can be “fooled” into misclassifying an input sample that has been minimally modified in a specific way. These modified samples are known as adversarial examples and have been crafted with the goal of causing the target DNN to …
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Human iris categorization using artificial neural networks
… of iris image categorization using artificial neural networks, specifically for human iris images with discernible and complicated textures. The work will allow users to quickly and automatically categorize human iris images by using supervised and unsupervised learning algorithms. …
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Using artificial neural networks to forecast changes in national and regional price indices for the UK residential property market
… This research examined the use of artificial neural networks, trained usingnational economic, social and residential property transaction time-series data, toforecast trends within the housing market.Artificial neural networks have previously been applied successfully to produceestimates of …
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A study on the effect of target object size in object detection
… through the use of Region-based Convolutional Neural Networks (RCNN). Studies have been carried out to improve object detection models. However, the detection of small objects still poses numerous challenges for the said models. Small object detection is considered as one of the biggest …
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Monitoring and anomaly detection in solar thermal systems using adaptive resonance theory neural networks
… control. Adaptive Resonance Theory (ART)-based neural networks are chosen to perform this task, because the ART-based neural networks are fast, efficient learners and retain memory while learning new patterns. In particular, the ART networks can be incorporated into SHW system controller without …
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Fuzzy neural networks
Since the development of computer technology, methods have been developed and investigated to mimic the processes of the human brain. The human brain is a collection of billions of neurons interconnected with each other. Interconnected neurons are modeled with artificial neural networks (ANNs or …
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