Search for dissertations about: "neural networks implementation to computer"
Showing result 1 - 5 of 21 swedish dissertations containing the words neural networks implementation to computer.
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1. Efficient Document Image Binarization using Heterogeneous Computing and Interactive Machine Learning
Abstract : Large collections of historical document images have been collected by companies and government institutions for decades. More recently, these collections have been made available to a larger public via the Internet. However, to make accessing them truly useful, the contained images need to be made readable and searchable. READ MORE
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2. Automated CNN pipeline generation for heterogeneous architectures
Abstract : Heterogeneity is a vital feature in emerging processor chip designing. Asymmetric multicore-clusters such as high-performance cluster and power efficient cluster are common in modern edge devices. One example is Intel's Alder Lake featuring Golden Cove high-performance cores and Gracemont power-efficient cores. READ MORE
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3. Highway Traffic State Estimation and Short-term Prediction
Abstract : Traffic congestion is increasing in almost all large cities, leading to a number of negative effects such as pollution and delays. However, building new roads is not a feasible solution. Instead, the use of the existing road network has to be optimized, together with a shift towards more sustainable transport modes. READ MORE
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4. DeepMaker : Customizing the Architecture of Convolutional Neural Networks for Resource-Constrained Platforms
Abstract : Convolutional Neural Networks (CNNs) suffer from energy-hungry implementation due to requiring huge amounts of computations and significant memory consumption. This problem will be more highlighted by the proliferation of CNNs on resource-constrained platforms in, e.g., embedded systems. READ MORE
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5. An Attractor Memory Model of Neocortex
Abstract : This thesis presents an abstract model of the mammalian neocortex. The model was constructed by taking a top-down view on the cortex, where it is assumed that cortex to a first approximation works as a system with attractor dynamics. READ MORE
