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» Multiple target detection using Bayesian learning
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UAI
1996
13 years 11 months ago
Bayesian Learning of Loglinear Models for Neural Connectivity
This paper presents a Bayesian approach to learning the connectivity structure of a group of neurons from data on configuration frequencies. A major objective of the research is t...
Kathryn B. Laskey, Laura Martignon
FCCM
1998
IEEE
169views VLSI» more  FCCM 1998»
14 years 2 months ago
Scalable Network Based FPGA Accelerators for an Automatic Target Recognition Application
Abstract Image processing, specifically Automatic Target Recognition (ATR) in Synthetic Aperture Radar (SAR) imagery, is an application area that can require tremendous processing ...
Ruth Sivilotti, Young Cho, Wen-King Su, Danny Cohe...
BMCBI
2006
127views more  BMCBI 2006»
13 years 10 months ago
PathogenMIPer: a tool for the design of molecular inversion probes to detect multiple pathogens
Background: Here we describe PathogenMIPer, a software program for designing molecular inversion probe (MIP) oligonucleotides for use in pathogen identification and detection. The...
Sreedevi Thiyagarajan, Miloslav Karhanek, Michael ...
ICCV
2009
IEEE
15 years 2 months ago
Adaptive Fragments-Based Tracking of Non-Rigid Objects Using Level Sets
We present an approach to visual tracking based on dividing a target into multiple regions, or fragments. The target is represented by a Gaussian mixture model in a joint feature...
Prakash Chockalingam, Nalin Pradeep
ICML
2009
IEEE
14 years 10 months ago
A majorization-minimization algorithm for (multiple) hyperparameter learning
We present a general Bayesian framework for hyperparameter tuning in L2-regularized supervised learning models. Paradoxically, our algorithm works by first analytically integratin...
Chuan-Sheng Foo, Chuong B. Do, Andrew Y. Ng