Essays about: "Neuralt faltningsnätverk"
Showing result 1 - 5 of 9 essays containing the words Neuralt faltningsnätverk.
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1. Deep Neural Networks as SurrogateModels for Fuel Performance Codes
University essay from Uppsala universitet/Tillämpad kärnfysikAbstract : The core component of a nuclear power plant is the reactor and the fuel rods that supply it with fission fuel. Efficient and safe energy extraction is thus highly dependent on the reactor design and the conditions of the fuel rods. To anticipate high-quality operation and potential risks in advance, one must perform simulations on the fuel rods. READ MORE
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2. A Comparative Study of Machine Learning Algorithms for Angular Position Estimation in Assembly Tools
University essay from KTH/Matematisk statistikAbstract : The threaded fastener is by far the most common method for securing components together and plays a significant role in determining the quality of a product. Atlas Copco offers industrial tools for tightening these fasteners, which are today suffering from errors in the applied torque. READ MORE
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3. Particle Filter Bridge Interpolation in GANs
University essay from KTH/Matematisk statistikAbstract : Generative adversarial networks (GANs), a type of generative modeling framework, has received much attention in the past few years since they were discovered for their capacity to recover complex high-dimensional data distributions. These provide a compressed representation of the data where all but the essential features of a sample is extracted, subsequently inducing a similarity measure on the space of data. READ MORE
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4. Reduction of Common Operations in a Neural Network
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Machine learning models are becoming increasingly complex, and particularly artificial neural networks. Meanwhile, solutions are moving closer towards the edge with implementations on devices such as smartphones, TVs and cameras. This creates a demand for efficient models that perform well despite restricted computational resources. READ MORE
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5. Hyperparameter Optimization for Convolutional Neural Networks
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Training algorithms for artificial neural networks depend on parameters called the hyperparameters. They can have a strong influence on the trained model but are often chosen manually with trial and error experiments. READ MORE