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A fast neural network-based detection and tracking of dim moving targets in FLIR imagery
Usually the targets in forward looking infra-red imagery are dim, slowly moving, and buried under clutter and noise. Detecting and tracking of such targets is a challenging task. Although artificial neural networks (ANNs) have been used to solve this problem, they need a lot of training time. In ord...
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| container_end_page | 3149 vol. 5 |
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| container_start_page | 3144 |
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| container_volume | 5 |
| creator | Patra, J.C. Widjaja, F. Das, A. Ee Luang Ang |
| description | Usually the targets in forward looking infra-red imagery are dim, slowly moving, and buried under clutter and noise. Detecting and tracking of such targets is a challenging task. Although artificial neural networks (ANNs) have been used to solve this problem, they need a lot of training time. In order to reduce the training time, we propose principal component analysis as a dimension reduction technique. We used an MLP with LM learning algorithm and a RBF neural network (RBFNN) with K-means algorithm to cluster the data. Both the ANNs are used in a neural adaptive line enhancer (NALE) configuration. Extensive computer simulations showed the combination of PCA and ANNs gives satisfactory results with significant reduction in training time. |
| doi_str_mv | 10.1109/IJCNN.2005.1556430 |
| format | conference_proceeding |
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Detecting and tracking of such targets is a challenging task. Although artificial neural networks (ANNs) have been used to solve this problem, they need a lot of training time. In order to reduce the training time, we propose principal component analysis as a dimension reduction technique. We used an MLP with LM learning algorithm and a RBF neural network (RBFNN) with K-means algorithm to cluster the data. Both the ANNs are used in a neural adaptive line enhancer (NALE) configuration. Extensive computer simulations showed the combination of PCA and ANNs gives satisfactory results with significant reduction in training time.</abstract><pub>IEEE</pub><doi>10.1109/IJCNN.2005.1556430</doi></addata></record> |
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| identifier | ISSN: 2161-4393 |
| ispartof | Proceedings. 2005 IEEE International Joint Conference on Neural Networks, 2005, 2005, Vol.5, p.3144-3149 vol. 5 |
| issn | 2161-4393 2161-4407 |
| language | eng |
| recordid | cdi_ieee_primary_1556430 |
| source | IEEE Electronic Library (IEL) Conference Proceedings |
| subjects | Artificial neural networks Clustering algorithms Intelligent networks Line enhancers Neural networks Object detection Principal component analysis Real time systems Sonar Target tracking |
| title | A fast neural network-based detection and tracking of dim moving targets in FLIR imagery |
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