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 10 of 10 for “"one-shot learning"”.
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Active one-shot learning for personalized human affect estimation
… classify human affect leads to the challenge of learning on data that is complex in features and limited in size and labels. How can these models balance being general and personalized, capturing both the commonalities and the individual quirks of people? While previous research has explored the …
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One-Shot Learning Model for Cancer Diagnosis from Histopathological Images
… is tedious, time consuming, subjective, error prone and lacks inter-pathologist agreement. Thousands of patients are misdiagnosed each year, and several automated image analysis techniques using Deep Neural Networks (DNN) have been proposed for analyzing histopathology images for various cancer …
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Invariance properties of the human visual system in one-shot learning
… characterizes human invariant recognition in one-shot learning. By using novel stimuli, we address the question whether invariance to transformation emerges from experience and memorization of templates or from the brain instantly computing invariant representation. Our psychophysical …
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Interpretable neural networks via alignment and dpstribution Propagation
… three types of problems where data is limited - one-shot learning and open-set recognition in the one-shot setting, unsupervised learning, and classification with missing data. The first setting of limited data that we tackle is when there are only few examples per object type. During object …
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Discovering linguistic structures in speech : models and applications
… framework for automatically acquiring a phone-like inventory of a language. In addition, we integrate our phone discovery model with adaptor grammars, a nonparametric Bayesian extension of probabilistic context-free grammars, to induce hierarchical linguistic structures, including sub-word …
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Vision-Based Force Planning and Voice-Based Human-Machine Interface of an Assistive Robotic Exoskeleton Glove for Brachial Plexus Injuries
… which was then complemented by an innovative one-shot learning-based alternative, which proved to be more effective than CVASV in terms of training time and connectivity requirements. Clinical trials were conducted successfully in patients with BPI, demonstrating the effectiveness of the …
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Learning Generative Models Using Structured Latent Variables
Recent machine learning advances in computer vision and speech recognition have been largely driven by the application of supervised neural networks on large labeled datasets, leveraging effective regularization techniques and architectural design. Using more data and computational resources, …
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Device-Free WiFi Sensing for Human Activity Recognition
… intelligent monitoring. Recently, applying deep learning (DL) to WiFi-based HAR has received strong research interest. Assisted by signal processing techniques, DL-based HAR methods are able to automatically extract deep features from input signals, contributing to successful recognitions. …
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Constructive spiking neural networks for simulations of neuroplasticity
… neural networks are important tools in machine learning and neuroscience; however, a difficult step in their implementation is the selection of the neural network size and structure. This thesis develops fundamental theory on algorithms for constructing neurons in spiking neural networks and …
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Towards more human-like concept learning in machines : compositionality, causality, and learning-to-learn
… from just a single example, yet machine learning algorithms typically require hundreds or thousands of examples to perform similarly. People can also use their learned concepts in richer ways than conventional machine learning systems - for action, imagination, and explanation suggesting …