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CVPR
2012
IEEE
11 years 10 months ago
Batch mode Adaptive Multiple Instance Learning for computer vision tasks
Multiple Instance Learning (MIL) has been widely exploited in many computer vision tasks, such as image retrieval, object tracking and so on. To handle ambiguity of instance label...
Wen Li, Lixin Duan, Ivor Wai-Hung Tsang, Dong Xu
QRE
2010
129views more  QRE 2010»
13 years 6 months ago
Improving quality of prediction in highly dynamic environments using approximate dynamic programming
In many applications, decision making under uncertainty often involves two steps- prediction of a certain quality parameter or indicator of the system under study and the subseque...
Rajesh Ganesan, Poornima Balakrishna, Lance Sherry
IPPS
1998
IEEE
13 years 11 months ago
A Resource Management Model for Dynamic, Scalable, Dependable, Real-Time Systems
Abstract. Dynamic real-time systems function in unpredictable environments and have requirements that span many domains such as time, survivability, and scalability. The system req...
Binoy Ravindran, Lonnie R. Welch, Carl Bruggeman, ...
IPPS
2000
IEEE
13 years 12 months ago
Quality of Service Negotiation for Distributed, Dynamic Real-Time Systems
Dynamic, distributed, real-time systems control an environment that varies widely without any time-invariant statistical or deterministic characteristic, are spread across multiple...
Charles Cavanaugh, Lonnie R. Welch, Behrooz Shiraz...
IPPS
1999
IEEE
13 years 11 months ago
DynBench: A Dynamic Benchmark Suite for Distributed Real-Time Systems
In this paper we present the architecture and framework for a benchmark suite that has been developed as part of the DeSiDeRaTa project. The proposed benchmark suite is representat...
Behrooz Shirazi, Lonnie R. Welch, Binoy Ravindran,...