Search for dissertations about: "Gabriel Eilertsen"
Found 5 swedish dissertations containing the words Gabriel Eilertsen.
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1. The high dynamic range imaging pipeline : Tone-mapping, distribution, and single-exposure reconstruction
Abstract : Techniques for high dynamic range (HDR) imaging make it possible to capture and store an increased range of luminances and colors as compared to what can be achieved with a conventional camera. This high amount of image information can be used in a wide range of applications, such as HDR displays, image-based lighting, tone-mapping, computer vision, and post-processing operations. READ MORE
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2. Inverse Problems for Tumour Growth Models and Neural ODEs
Abstract : This thesis concerns the application of methods and techniques from the theory of inverse problems and differential equations to study models arising in the areas of mathematical oncology and deep learning. The first problem studied is to develop methods to perform numerical simulations with full 3-dimensional brain imaging data of reaction-diffusion models for tumour growth forwards as well as backwards in time with the goal of enabling the numerical reconstruction of the source of the tumour given an image (or similar data) at a later stage in time of the tumour. READ MORE
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3. Generalisation and reliability of deep learning for digital pathology in a clinical setting
Abstract : Deep learning (DL) is a subfield of artificial intelligence (AI) focused on developing algorithms that learn from data to perform some tasks that can aid humans in their daily life or work assignments. Research demonstrates the potential of DL in supporting pathologists with routine tasks like detecting breast cancer metastases and grading prostate cancer. READ MORE
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4. Deep Learning for Digital Pathology in Limited Data Scenarios
Abstract : The impressive technical advances seen for machine learning algorithms in combination with the digitalization of medical images in the radiology and pathology departments show great promise in introducing powerful image analysis tools for image diagnostics. In particular, deep learning, a subfield within machine learning, has shown great success, advancing fields such as image classification and detection. READ MORE
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5. Synthetic data for visual machine learning : A data-centric approach
Abstract : Deep learning allows computers to learn from observations, or else training data. Successful application development requires skills in neural network design, adequate computational resources, and a training data distribution that covers the application do-main. READ MORE