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ESANN
2007
15 years 5 months ago
How to process uncertainty in machine learning?
Uncertainty is a popular phenomenon in machine learning and a variety of methods to model uncertainty at different levels has been developed. The aim of this paper is to motivate ...
Barbara Hammer, Thomas Villmann
ISCAPDCS
2007
15 years 5 months ago
Architectural requirements of parallel computational biology applications with explicit instruction level parallelism
—The tremendous growth in the information culture, efficient digital searches are needed to extract and identify information from huge data. The notion that evolution in silicon ...
Naeem Zafar Azeemi
DAC
2003
ACM
16 years 5 months ago
Compiler-generated communication for pipelined FPGA applications
In this paper, we describe a set of compiler analyses and an implementation that automatically map a sequential and un-annotated C program into a pipelined implementation, targete...
Heidi E. Ziegler, Mary W. Hall, Pedro C. Diniz
ICDAR
2003
IEEE
15 years 9 months ago
Automatic Feature Selection with Applications to Script Identification of Degraded Documents
Current approaches to script identification rely on hand-selected features and often require processing a significant part of the document to achieve reliable identification. We p...
Vitaly Ablavsky, Mark R. Stevens
ICIP
2000
IEEE
15 years 8 months ago
Low-Complexity Global Motion Estimation from P-Frame Motion Vectors for MPEG-7 Applications
In this contribution, we present an algorithm for lowcomplexity global motion estimation, that works with block-coded video (e.g. MPEG-2). A superimposed global motion model is fi...
Aljoscha Smolic, Michael Hoeynck, Jens-Rainer Ohm