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» A Framework for Exploring Optimization Properties
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ENTCS
2007
121views more  ENTCS 2007»
13 years 8 months ago
Incremental Parametric Development of Greedy Algorithms
The event B method provides a general framework for modelling both data structures and algorithms. B models are validated by discharging proof obligations ensuring safety properti...
Dominique Cansell, Dominique Méry
ICCV
2011
IEEE
12 years 8 months ago
Strong Supervision From Weak Annotation: Interactive Training of Deformable Part Models
We propose a framework for large scale learning and annotation of structured models. The system interleaves interactive labeling (where the current model is used to semiautomate t...
Steven Branson, Pietro Perona, Serge Belongie
TSE
2002
122views more  TSE 2002»
13 years 8 months ago
Virtual Benchmarking and Model Continuity in Prototyping Embedded Multiprocessor Signal Processing Systems
The complexity of hardware/software codesign of embedded real-time signal processing systems can be reduced by rapid system prototyping (RSP). However, existing RSP frameworks do n...
Randall S. Janka, Linda M. Wills, Lewis B. Baumsta...
JUCS
2006
112views more  JUCS 2006»
13 years 8 months ago
A Multi-objective Genetic Approach to Mapping Problem on Network-on-Chip
Abstract: Advances in technology now make it possible to integrate hundreds of cores (e.g. general or special purpose processors, embedded memories, application specific components...
Giuseppe Ascia, Vincenzo Catania, Maurizio Palesi
GECCO
2004
Springer
148views Optimization» more  GECCO 2004»
14 years 2 months ago
A Multi-objective Approach to Configuring Embedded System Architectures
Portable embedded systems are being driven by consumer demands to be thermally efficient, perform faster, and have longer battery life. To design such a system, various hardware un...
James Northern III, Michael A. Shanblatt