Search for dissertations about: "Histogram"
Showing result 1 - 5 of 54 swedish dissertations containing the word Histogram.
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1. Random Forest for Histogram Data : An application in data-driven prognostic models for heavy-duty trucks
Abstract : Data mining and machine learning algorithms are trained on large datasets to find useful hidden patterns. These patterns can help to gain new insights and make accurate predictions. Usually, the training data is structured in a tabular format, where the rows represent the training instances and the columns represent the features of these instances. READ MORE
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2. Learning Decision Trees and Random Forests from Histogram Data : An application to component failure prediction for heavy duty trucks
Abstract : A large volume of data has become commonplace in many domains these days. Machine learning algorithms can be trained to look for any useful hidden patterns in such data. Sometimes, these big data might need to be summarized to make them into a manageable size, for example by using histograms, for various reasons. READ MORE
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3. Discrete Scale-Space Theory and the Scale-Space Primal Sketch
Abstract : This thesis, within the subfield of computer science known as computer vision, deals with the use of scale-space analysis in early low-level processing of visual information. The main contributions comprise the following five subjects:The formulation of a scale-space theory for discrete signals. READ MORE
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4. Applications of diffusion MRI: Tensor-valued encoding, time-dependent diffusion, and histological validation
Abstract : Diffusion MRI (dMRI) sensitizes the MR signal to the diffusion of water molecules at the microscopic level and thereby non-invasively probes tissue microstructure. This is relevant when determining biological properties of tissues, for example, cancer type and its malignancy. READ MORE
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5. Image and Data Analysis for Biomedical Quantitative Microscopy
Abstract : This thesis presents automatic image and data analysis methods to facilitate and improve microscopy-based research and diagnosis. New technologies and computational tools are necessary for handling the ever-growing amounts of data produced in life science. READ MORE