| 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.
Seeded Ising Model for Human Iris Templates and Secure Distributed Iris Recognition
<학부생을 위한 ɛ 강연> 4차 산업혁명, 글로벌 디지털 혁신과 일자리 전쟁, 대학의 역할
An equivalent condition to Bohr's for Dirichlet series
On the Schauder theory for elliptic PDEs
<학부생을 위한 ɛ 강연> 서비스 진보의 관점에서 본 AI technology
Seifert fiberings
Mixing time of random processes
Periodic orbits in symplectic geometry
<학부생을 위한 ɛ 강연> 196884=196883+1
Mathematical Models and Intervention Strategies for Emerging Infectious Diseases: MERS, Ebola and 2009 A/H1N1 Influenza
Convex and non-convex optimization methods in image processing
Creation of concepts for prediction models and quantitative trading
<학부생을 위한 ɛ 강연> Introduction to the incompressible Navier-Stokes equations
An introduction to hyperplane arrangements
What happens inside a black hole?
<학부생을 위한 ε 강연> Variable-driven sociological research with data innovations
Subword complexity, expansion of real numbers and irrationality exponents
<학부생을 위한 ε 강연> 동형암호와 근사정수론
4-manifold topology and disk embedding
Hybrid discontinuous Galerkin methods in computational science and engineering
