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IJPRAI
1998
100views more  IJPRAI 1998»
15 years 8 days ago
Obtaining The Correspondence between Bayesian and Neural Networks
We present in this paper a novel method for eliciting the conditional probability matrices needed for a Bayesian network with the help of a neural network. We demonstrate how we c...
Athena Stassopoulou, Maria Petrou
89
Voted
IDMS
1998
Springer
100views Multimedia» more  IDMS 1998»
15 years 4 months ago
Network-Conscious Compressed Images over Wireless Networks
We apply the concept of network-consciousness to image compression, an approach that does not simply optimize compression, but which optimizes overall performance when compressed i...
Sami Iren, Paul D. Amer, Phillip T. Conrad
CORR
2008
Springer
167views Education» more  CORR 2008»
15 years 20 days ago
Energy Scaling Laws for Distributed Inference in Random Networks
The energy scaling laws of multihop data fusion networks for distributed inference are considered. The fusion network consists of randomly located sensors independently distributed...
Animashree Anandkumar, Joseph E. Yukich, Lang Tong...
84
Voted
DATE
2009
IEEE
119views Hardware» more  DATE 2009»
15 years 7 months ago
On-chip communication architecture exploration for processor-pool-based MPSoC
— MPSoC is evolving towards processor-pool (PP)-based architectures, which employ hierarchical on-chip network for inter- and intra-PP communication. Since the design space of PP...
Young-Pyo Joo, Sungchan Kim, Soonhoi Ha
WAPCV
2004
Springer
15 years 6 months ago
Learning of Position-Invariant Object Representation Across Attention Shifts
Abstract. Selective attention shift can help neural networks learn invariance. We describe a method that can produce a network with invariance to changes in visual input caused by ...
Muhua Li, James J. Clark