Artificial Neural Networks
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Publisher
Springer International Publishing
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-41337-7_6
Reference10 articles.
1. Abiodun, O. I., A. Jantan, A. E. Omolara, K. V. Dada, N. A. Mohamed, & H. Arshad. (2018). State-of-the-art in artificial neural network applications: A survey. Heliyon, 4(11), e00938. https://www.sciencedirect.com/science/article/pii/S2405844018332067.
2. Abiodun, O. I., M. U. Kiru, A. Jantan, A. E. Omolara, K. V. Dada, A. M. Umar, O. U. Linus, H. Arshad, A. A. Kazaure, & U. Gana. (2019). Comprehensive Review of Artificial Neural Network Applications to Pattern Recognition. IEEE Access, 7, 158820–158846. https://doi.org/10.1109/ACCESS.2019.2945545.
3. Baptista, D., & Dias, F. M. (2013). A survey of artificial neural network training tools. Neural Computer Application, 23(3–4), 609–615. http://dblp.uni-trier.de/db/journals/nca/nca23.html#BaptistaD13a.
4. Hastie, T., Tibshirani, R., & Friedman, J. (2009). The Elements of Statistical Learning: Data Mining, Inference, and Prediction (2nd ed.). Springer Series in Statistics, New York: Springer. https://www.springer.com/gp/book/9780387848570.
5. Lörincz, A. (2011). Learning the states: A brain inspired neural model. In J. Schmidhuber, K. R. Thórisson & M. Looks (Eds.) AGI vol. 6830 of Lecture Notes in Computer Science (pp. 315–320). Springer.
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