Zobrazeno 1 - 6
of 6
pro vyhledávání: '"Scott A. Musman"'
Publikováno v:
Artificial Intelligence and Machine Learning for Multi-Domain Operations Applications.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::85b5b368a3f1d39c0382adc320960a46
https://doi.org/10.1117/12.2518976
https://doi.org/10.1117/12.2518976
Publikováno v:
Neural Networks. 7:709-728
A comparison of the unsupervised Projection Pursuit learning algorithm (BCM), with supervised backward propagation (BP) and a laterally inhibited version of BP (LIBP) was performed. Simulated inverse synthetic aperature radar (ISAR) presentations ser
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::92dc68755692b06bf8e31038d4c9be22
https://doi.org/10.1016/0893-6080(94)90047-7
https://doi.org/10.1016/0893-6080(94)90047-7
Publikováno v:
International Journal of Pattern Recognition and Artificial Intelligence. :513-526
Many classification problems must be performed in a timely or time constrained manner. For this reason, the generation of control schemes which are capable of responding in real-time are fundamental to many applications. For our problem, that of ship
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::52871f6a4537ba548027e861fb694065
https://doi.org/10.1142/s0218001493000261
https://doi.org/10.1142/s0218001493000261
Publikováno v:
Neural Networks for Signal Processing II Proceedings of the 1992 IEEE Workshop.
The use of neural networks for the classification of simulated inverse synthetic aperture radar imagery is investigated. Symmetries of the artificial imagery make the use of localized moments a convenient preprocessing tool for the inputs to a neural
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::cda361d8facc9008731d5c0c3bc72101
https://doi.org/10.1109/nnsp.1992.253685
https://doi.org/10.1109/nnsp.1992.253685
Inverse synthetic aperture radar (ISAR) produces images of ships at sea which human operators can be trained to recognize. Because ISAR uses the ship's own varying angular motions (roll, pitch, and yaw) for cross-range resolution, the viewing aspect
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ddc1c4b88bcb7d54470bb8750bf5c013
https://zenodo.org/record/1262436
https://zenodo.org/record/1262436
Conference
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