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» Limits of Learning-Based Superresolution Algorithms
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ICASSP
2011
IEEE
12 years 9 months ago
Fully non-local super-resolution via spectral hashing
Super-resolution is the task of creating an high resolution image from a low resolution input sequence. To overcome the difficulties of fine image registration, several methods ...
Emmanuel d'Angelo, Pierre Vandergheynst
ICPR
2004
IEEE
14 years 6 months ago
An Iris Image Synthesis Method Based on PCA and Super-Resolution
It is very important for the performance evaluation of iris recognition algorithms to construct very large iris databases. However, limited by the real conditions, there are no ve...
Jiali Cui, JunZhou Huang, Tieniu Tan, Yunhong Wang...
ARC
2008
Springer
186views Hardware» more  ARC 2008»
13 years 7 months ago
FPGA-based Real-time Super-Resolution on an Adaptive Image Sensor
Recent technological advances in imaging industry have lead to the production of imaging systems with high density pixel sensors. However, their long exposure times limit their app...
Maria E. Angelopoulou, Christos-Savvas Bouganis, P...
ICANNGA
2007
Springer
153views Algorithms» more  ICANNGA 2007»
13 years 7 months ago
A Neural Framework for Robot Motor Learning Based on Memory Consolidation
Neural networks are a popular technique for learning the adaptive control of non-linear plants. When applied to the complex control of android robots, however, they suffer from se...
Heni Ben Amor, Shuhei Ikemoto, Takashi Minato, Ber...
ICDCS
2007
IEEE
13 years 11 months ago
Testing Security Properties of Protocol Implementations - a Machine Learning Based Approach
Security and reliability of network protocol implementations are essential for communication services. Most of the approaches for verifying security and reliability, such as forma...
Guoqiang Shu, David Lee