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» Nonlinear principal component analysis of noisy data
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IMC
2005
ACM
15 years 3 months ago
Network Anomography
Anomaly detection is a first and important step needed to respond to unexpected problems and to assure high performance and security in IP networks. We introduce a framework and ...
Yin Zhang, Zihui Ge, Albert G. Greenberg, Matthew ...
ISBI
2004
IEEE
15 years 10 months ago
Clustering-Based Framework for Comparing fMRI Analysis Methods
In this paper, a cluster-based framework is introduced for comparing analysis methods of functional magnetic resonance images (fMRI). In the proposed framework, fMRI data is repla...
Hamid Soltanian-Zadeh, Gholam-Ali Hossein-Zadeh, A...
BMVC
2000
14 years 11 months ago
Data and Decision Level Fusion of Temporal Information for Automatic Target Recognition
Automatic Target Recognition (ATR) is a demanding application that requires separation of targets from a noisy background in a sequence of images. In our previous work [5] the bac...
Kieron Messer, Josef Kittler
NIPS
1993
14 years 11 months ago
Analyzing Cross-Connected Networks
The non-linear complexities of neural networks make network solutions difficult to understand. Sanger's contribution analysis is here extended to the analysis of networks aut...
Thomas R. Shultz, Jeffrey L. Elman
IPMI
2001
Springer
15 years 10 months ago
Feature Enhancement in Low Quality Images with Application to Echocardiography
In this paper we propose a novel approach to feature enhancement to enhance the quality of noisy images. Our approach is based on a phase-based feature detection algorithm, followe...
Djamal Boukerroui, J. Alison Noble, Michael Brady