Search for dissertations about: "Convolutional Neural Networks"
Showing result 6 - 10 of 72 swedish dissertations containing the words Convolutional Neural Networks.
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6. Equivariant Neural Networks for Biomedical Image Analysis
Abstract : While artificial intelligence and deep learning have revolutionized many fields in the last decade, one of the key drivers has been access to data. This is especially true in biomedical image analysis where expert annotated data is hard to come by. READ MORE
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7. 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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8. Uncertainty-Aware Convolutional Neural Networks for Vision Tasks on Sparse Data
Abstract : Early computer vision algorithms operated on dense 2D images captured using conventional monocular or color sensors. Those sensors embrace a passive nature providing limited scene representations based on light reflux, and are only able to operate under adequate lighting conditions. READ MORE
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9. Convolutional Network Representation for Visual Recognition
Abstract : Image representation is a key component in visual recognition systems. In visual recognition problem, the solution or the model should be able to learn and infer the quality of certain visual semantics in the image. READ MORE
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10. Pith location and annual ring detection for modelling of knots and fibre orientation in structural timber : A Deep-Learning-Based Approach
Abstract : Detection of pith, annual rings and knots in relation to timber board cross-sections is relevant for many purposes, such as for modelling of sawn timber and for real-time assessment of strength, stiffness and shape stability of wood materials. However, the methods that are available and implemented in optical scanners today do not always meet customer accuracy and/or speed requirements. READ MORE