|
|
Bacteria Classification Based on Marker Genes
Pelantová, Lucie ; Hon, Jiří (referee) ; Smatana, Stanislav (advisor)
The aim of this work is proposal of new method for bacteria classification based on sequences of marker genes. For this purpose was chosen 10 marker genes. Resulting MultiGene classifier processes data set by dividing it in several groups and choosing gene for each group which can distinguish this group with best results. This work describes implementation of MultiGene classifier and its results in comparison with other bacteria classifiers and with classification based entirely on gene 16S rRNA.
|
|
|
Automatic Processing of Tests Corrected by Hand
Pelantová, Lucie ; Herout, Adam (referee) ; Beran, Vítězslav (advisor)
The aim of this bachelor's thesis is mass processing of exams corrected by hand. The essence of proposed solution is table detection. Structure of table is first detected in sample page, then this pattern is searched in processed page. Corresponding parts of table are used to compute homography. After application of transformation matrix are data segmented and send for handwritten text recognition. The thesis contains evaluation of accuracy for individual system components and possibility of use in practice. Resulting application is supposed to effectively segment data from structured documents.
|
|
|
Bacteria Classification Based on Marker Genes
Pelantová, Lucie ; Hon, Jiří (referee) ; Smatana, Stanislav (advisor)
The aim of this work is proposal of new method for bacteria classification based on sequences of marker genes. For this purpose was chosen 10 marker genes. Resulting MultiGene classifier processes data set by dividing it in several groups and choosing gene for each group which can distinguish this group with best results. This work describes implementation of MultiGene classifier and its results in comparison with other bacteria classifiers and with classification based entirely on gene 16S rRNA.
|
|
|
Automatic Processing of Tests Corrected by Hand
Pelantová, Lucie ; Herout, Adam (referee) ; Beran, Vítězslav (advisor)
The aim of this bachelor's thesis is mass processing of exams corrected by hand. The essence of proposed solution is table detection. Structure of table is first detected in sample page, then this pattern is searched in processed page. Corresponding parts of table are used to compute homography. After application of transformation matrix are data segmented and send for handwritten text recognition. The thesis contains evaluation of accuracy for individual system components and possibility of use in practice. Resulting application is supposed to effectively segment data from structured documents.
|
guest ::
