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Extra Form
Lecturer Michael Ng
Dept. Hong Kong Baptist University
date Apr 13, 2017

In this talk, we discuss some results of convex and non-convex optimization methods in image processing. Examples including image colorization, blind decovolution and impulse noise removal are presented to demonstrate these methods. Their advantages and disadvantages of using these methods are also illustrated.  


Atachment
Attachment '1'
  1. Existence of positive solutions for φ-Laplacian systems

  2. Essential dimension of simple algebras

  3. Equations defining algebraic curves and their tangent and secant varieties

  4. Entropy of symplectic automorphisms

  5. Entropies on covers of compact manifolds

  6. Elliptic equations with singular drifts in critical spaces

  7. Diophantine equations and moduli spaces with nonlinear symmetry

  8. Descent in derived algebraic geometry

  9. Deformation spaces of Kleinian groups and beyond

  10. Creation of concepts for prediction models and quantitative trading

  11. Counting number fields and its applications

  12. Counting circles in Apollonian circle packings and beyond

  13. 18Apr
    by 김수현
    in Math Colloquia

    Convex and non-convex optimization methods in image processing

  14. Contact topology of singularities and symplectic fillings

  15. Contact instantons and entanglement of Legendrian links

  16. Contact Homology and Constructions of Contact Manifolds

  17. Conservation laws and differential geometry

  18. Connes's Embedding Conjecture and its equivalent

  19. Connectedness of a zero-level set as a geometric estimate for parabolic PDEs

  20. Congruences between modular forms

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