The program of the 6th edition of the Spring School of Image Processing will consist mainly of tutorial talks given by organizers from the Department of Image Processing (ÚTIA) and participating Ph.D. students:
Morning | Evening | |
su (ne) | ------------------------- | Welcome party |
mo (po) | Feature transforms I Irena Váňová: Introduction to feature transforms (PCA, LDA, kernel PCA, kernel Fisher's discriminant) |
Feature selection Petr Somol: Feature Selection Criteria - An Overview Pattern recognition I Jan Flusser: General theory of image recognition and registration (Introduction and criticism) |
tu (út) |
Feature transforms II Jan Kamenický: Manifold learning - LLE (Locally linear embedding), Isomap |
Applications I Václav Šmídl: Probabilistic model for analysis of kidney image sequences |
we (st) | Applications II Jan Schier: Image processing for selected biological experiments |
Feature transforms III Lubomír Soukup: Feature transform by non-parametric mutual information maximization |
th (čt) | Orthogonal polynomials Tomáš Suk: Orthogonal polynomials and their use in image processing |
Feature transforms IV Jiří Sedlář: HLDA (Heteroscedastic LDA), SDA (Subclass discriminant analysis) |
fr (pá) | Image retrieval Filip Šroubek: Locally adaptive regression kernels for vision |
If you have any questions or comments, contact Michal Šorel