The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.
Artificial neural networks: a tutorial
Abstract
Artificial neural nets (ANNs) are massively parallel systems with large numbers of interconnected simple processors. The article discusses the motivations behind the development of ANNs and describes the basic biological neuron and the artificial computational model. It outlines network architectures and learning processes, and presents some of the most commonly used ANN models. It concludes with character recognition, a successful ANN application.
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Citations
Cites
Neural networks and physical systems with emergent collective computational abilities.
Hopfield, J. J. (1982) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.79.8.2554 · Cited by 19,270
A logical calculus of the ideas immanent in nervous activity
McCulloch, W. S., & Pitts, W. (1943) · The Bulletin of Mathematical Biophysics · doi:10.1007/bf02478259 · Cited by 18,566
Backpropagation Applied to Handwritten Zip Code Recognition
LeCun, Y., Boser, B., Denker, J. S., Henderson, D., Howard, R. E., Hubbard, W., & Jackel, L. D. (1989) · Neural Computation · doi:10.1162/neco.1989.1.4.541 · Cited by 11,891
Hebb, D. O. (2005) · doi:10.4324/9781410612403 · Cited by 9,825
Cited by
A Survey of Data Mining and Machine Learning Methods for Cyber Security Intrusion Detection
Buczak, A. L., & Guven, E. (2016) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2015.2494502 · Cited by 3,332
Electricity price forecasting: A review of the state-of-the-art with a look into the future
Weron, R. (2014) · International Journal of Forecasting · doi:10.1016/j.ijforecast.2014.08.008 · Cited by 1,646
Chicco, D., Tötsch, N., & Jurman, G. (2021) · BioData Mining · doi:10.1186/s13040-021-00244-z · Cited by 893
Data-Driven Methods for Predictive Maintenance of Industrial Equipment: A Survey
Zhang, W., Yang, D., & Wang, H. (2019) · IEEE Systems Journal · doi:10.1109/jsyst.2019.2905565 · Cited by 732
Learning and selective attention
Dayan, P., Kakade, S., & Montague, P. R. (2000) · Nature Neuroscience · doi:10.1038/81504 · Cited by 495
Metadata
- Authors
- Jain, A. K., Mao, J., & Mohiuddin, K. M.
- Venue
- Computer
- Published
- 1996-03
- Volume
- 29
- Issue
- 3
- Pages
- 31-44
- ISSN
- 0018-9162 (ISSN-L)
- OpenAlex
- W2002016471
- Cited by
- 4,946
- References
- 4
- FWCI
- 84.59
- Type
- journal article
- Language
- en
- Open access
- closed
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Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
