| 강연자 | Michael Ng |
|---|---|
| 소속 | Hong Kong Baptist University |
| date | 2017-04-13 |
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.
Essential dimension of simple algebras
Equations defining algebraic curves and their tangent and secant varieties
Entropy of symplectic automorphisms
Entropies on covers of compact manifolds
Elliptic equations with singular drifts in critical spaces
Diophantine equations and moduli spaces with nonlinear symmetry
Descent in derived algebraic geometry
Deformation spaces of Kleinian groups and beyond
Creation of concepts for prediction models and quantitative trading
Counting number fields and its applications
Counting circles in Apollonian circle packings and beyond
Convex and non-convex optimization methods in image processing
Contact topology of singularities and symplectic fillings
Contact topology and the three-body problem
Contact instantons and entanglement of Legendrian links
Contact Homology and Constructions of Contact Manifolds
Conservation laws and differential geometry
Connes's Embedding Conjecture and its equivalent
Connectedness of a zero-level set as a geometric estimate for parabolic PDEs
Congruences between modular forms
