Sensor fusion for mine detection with the RNN
Publication
, Conference
Gelenbe, E; Koęak, T; Collins, L
Published in: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
January 1, 1997
In this paper we propose a neural network based approach to sensor fusion, to detect mine locations from electromagnetic induction (EMI) data. Our results use the Random Neural Network (RNN) model [2, 4, 5] which is closer to biophysical reality and mathematically more tractable than standard neural methods. The network is trained to produce an error minimizing non-linear mapping from three sensor output images to the fused image. The result is thresholded to point to likely mine locations.
Duke Scholars
Published In
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
DOI
EISSN
1611-3349
ISSN
0302-9743
ISBN
9783540636311
Publication Date
January 1, 1997
Volume
1327
Start / End Page
938 / 942
Related Subject Headings
- Artificial Intelligence & Image Processing
- 46 Information and computing sciences
Citation
APA
Chicago
ICMJE
MLA
NLM
Gelenbe, E., Koęak, T., & Collins, L. (1997). Sensor fusion for mine detection with the RNN. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 1327, pp. 938–942). https://doi.org/10.1007/bfb0020273
Gelenbe, E., T. Koęak, and L. Collins. “Sensor fusion for mine detection with the RNN.” In Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 1327:938–42, 1997. https://doi.org/10.1007/bfb0020273.
Gelenbe E, Koęak T, Collins L. Sensor fusion for mine detection with the RNN. In: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 1997. p. 938–42.
Gelenbe, E., et al. “Sensor fusion for mine detection with the RNN.” Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 1327, 1997, pp. 938–42. Scopus, doi:10.1007/bfb0020273.
Gelenbe E, Koęak T, Collins L. Sensor fusion for mine detection with the RNN. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 1997. p. 938–942.
Published In
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
DOI
EISSN
1611-3349
ISSN
0302-9743
ISBN
9783540636311
Publication Date
January 1, 1997
Volume
1327
Start / End Page
938 / 942
Related Subject Headings
- Artificial Intelligence & Image Processing
- 46 Information and computing sciences