Search for dissertations about: "pattern classification"

Showing result 1 - 5 of 168 swedish dissertations containing the words pattern classification.

  2. 1. Learning predictive models from graph data using pattern mining

    Author : Thashmee M. Karunaratne; Henrik Boström; Lars Asker; Nada Lavraˇc; Stockholms universitet; []
    Keywords : NATURVETENSKAP; NATURAL SCIENCES; Machine Learning; Graph Data; Pattern Mining; Classification; Regression; Predictive Models; Computer and Systems Sciences; data- och systemvetenskap;

    Abstract : Learning from graphs has become a popular research area due to the ubiquity of graph data representing web pages, molecules, social networks, protein interaction networks etc. However, standard graph learning approaches are often challenged by the computational cost involved in the learning process, due to the richness of the representation. READ MORE

  4. 2. Pattern Recognition Methods for Oral Lesion Classification using Digital Color Images

    Author : Artur Chodorowski; Chalmers tekniska högskola; []
    Keywords : TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; oral lesions; supervised classification; pattern recognition; computer-aided diagnosis; support vector machines; color; cancer; shape;

    Abstract : The present thesis addresses the development and application of pattern recognition methods for classification of oral lesions using digital color images as input. The human oral cavity is a site of numerous diseases and two of the common and visually similar lesions are oral leukoplakia and oral lichenoid reactions. READ MORE

  5. 3. Chemoenzymatic Resolution in Dynamic Systems : Screening, Classification and Asymmetric Synthesis

    Author : Yan Zhang; Olof Ramström; Sabine Flitsch; KTH; []
    Keywords : NATURVETENSKAP; NATURAL SCIENCES; constitutional dynamic chemistry; dynamic systemic resolution; dynamic kinetic resolution; enzyme catalysis; transesterification; enzyme promiscuity; asymmetric synthesis; pattern recognition; self-inhibition.;

    Abstract : This  thesis  is  divided  into  four  parts,  all  centered  around  Constitutional Dynamic  Chemistry  (CDC)  and  Dynamic  Kinetic  Resolution  (DKR)  using biocatalysts for selective transformations, and their applications in screening of bioactive compounds, organic synthesis, and enzyme classification.   In  part  one,  an  introduction  to  CDC  and  DKR  is  presented,  illustrating  the basic  concepts,  practical  considerations  and  potential  applications  of  such dynamic systems, thus providing the background information for the studies in the following chapters. READ MORE

  6. 4. Analysis of Metabolites in Complex Biological Samples Using LC/MS and Multivariate Data Analysis : Metabolic Fingerprinting and Detection of Biomarkers

    Author : Helena Idborg; Sven Jacobsson; Per-Olof Edlund; Jonas Bergquist; Stockholms universitet; []
    Keywords : NATURVETENSKAP; NATURAL SCIENCES; Metabolomics; Metabonomics; Metabolic Fingerprinting; Drug Metabolism; Biomarkers; Human Plasma; Rat Urine; LC MS; ZIC-HILIC; UPLC; UHPLC; ToF; Curve Resolution; Peak Detection; Pattern Recognition; Classification; PCA; PLS; PARAFAC; N-PLS; Data Fusion; Hierarchical Modeling; Batch modeling; Data Concatenation; Breast Cancer; Phospholipidosis; Analytical chemistry; Analytisk kemi; Analytical Chemistry; analytisk kemi;

    Abstract : To facilitate early diagnosis of diseases and elucidation of the processes involved in their development and progression, various specific compounds or ‘biomarkers’ are often monitored. The first step is to decide which compounds to analyze. READ MORE

  7. 5. Approximations of Bayes Classifiers for Statistical Learning of Clusters

    Author : Magnus Ekdahl; Timo Koski; Jukka Corander; Linköpings universitet; []
    Keywords : NATURVETENSKAP; NATURAL SCIENCES; Pattern Recognition; Stochastic Complexity; Naïve Bayes; Bayesian Network; Classification; Clustering; Chow-Liu trees; Mathematical statistics; Matematisk statistik;

    Abstract : It is rarely possible to use an optimal classifier. Often the classifier used for a specific problem is an approximation of the optimal classifier. Methods are presented for evaluating the performance of an approximation in the model class of Bayesian Networks. READ MORE