The DOI matches its Crossref record; 56 of the 56 references it cites were found in a registry or an index.
Survey of neural network technology for automatic target recognition
Abstract
A review is presented of ATR (automatic target recognition), and some of the highlights of neural network technology developments that have the potential for making a significant impact on ATR are presented. In particular, neural network technology developments in the areas of collective computation, learning algorithms, expert systems, and neurocomputer hardware could provide crucial tools for developing improved algorithms and computational hardware for ATR. The discussion covers previous ATR system efforts. ATR issues and needs, early vision and collective computation, learning and adaptation for ATR, feature extraction, higher vision and expert systems, and neurocomputer hardware.
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Cites
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Information fusion for wireless sensor networks: Methods, models, and classifications
Nakamura, E. F., Loureiro, A. A. F., & Frery, A. C. (2007) · ACM Computing Surveys · doi:10.1145/1267070.1267073 · Cited by 537
Automatic Target Recognition in Synthetic Aperture Radar Imagery: A State-of-the-Art Review
El-Darymli, K., Gill, E. W., Mcguire, P., Power, D., & Moloney, C. (2016) · IEEE Access · doi:10.1109/access.2016.2611492 · Cited by 388
A survey on hybrid human-artificial intelligence for autonomous driving
Ning, H., Yin, R., Ullah, A., & Shi, F. (2022) · IEEE Transactions on Intelligent Transportation Systems · doi:10.1109/tits.2021.3074695 · Cited by 84
Metadata
- Authors
- Roth, M. W.
- Venue
- IEEE Transactions on Neural Networks
- Published
- 1990-03
- Volume
- 1
- Issue
- 1
- Pages
- 28-43
- ISSN
- 1045-9227 (ISSN-L)
- OpenAlex
- W2050042584
- Cited by
- 268
- References
- 56
- FWCI
- 11.08
- Type
- journal article
- Language
- en
- Open access
- closed
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