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	Browse All Reviews > Computing Methodologies (I) > Pattern Recognition (I.5) > Models (I.5.1) > Neural Nets (I.5.1...)     Options: All Media Types Journals Proceedings Div Books Whole Books Other Date Reviewed Title Author Publisher Published Date Descending Ascending     1-10 of 30 Reviews about "Neural Nets (I.5.1...)": Date Reviewed   A deep learning technique for intrusion detection system using a recurrent neural networks based framework Kasongo S. Computer Communications 199113-125, 2023.  Type: Article So let’s assume you already know and understand that artificial intelligence’s main building blocks are perceptrons, that is, mathematical models of neurons. And you know that, while a single perceptron is too limited to get “int... Jan 19 2024   Visual and text sentiment analysis through hierarchical deep learning networks Chaudhuri A., Springer International Publishing, New York, NY, 2019. 120 pp.  Type: Book This book is on the extraction of sentiments from text/image data using machine learning. It describes research related to developing a deep learning technique for the extraction. The technique uses hierarchical gated feedback recurren... Jan 25 2021   Lie group machine learning Fanzhang L., Li Z., Zhao Z., Walter de Gruyter & Co., Berlin, Germany, 2018. 533 pp.  Type: Book (978-3-110500-68-4) Machine learning, one of the evergreen fields of electrical engineering, has recently gained momentum and has a number of new and innovative applications. Related fields, such as artificial intelligence, deep learning, brain learning, ... Dec 4 2019   Structured pruning of deep convolutional neural networks Anwar S., Hwang K., Sung W. ACM Journal on Emerging Technologies in Computing Systems 13(3): 1-18, 2017.  Type: Article A step toward improving the performance of deep learning by adding rules to node propagation, this paper is an interesting contribution to the area of neural networks.... Dec 20 2017   A deep convolutional neural network model to classify heartbeats Acharya U., Oh S., Hagiwara Y., Tan J., Adam M., Gertych A., Tan R. Computers in Biology and Medicine 89 389-396, 2017.  Type: Article Deep learning is one of the fastest growing areas of machine learning. With improvements in hardware technology, the use of deep learning algorithms is increasing daily. The emergence of deep learning has also led to the renaissance of... Dec 15 2017   Neural network based models for software effort estimation: a review Dave V., Dutta K. Artificial Intelligence Review 42(2): 295-307, 2014.  Type: Article Effort estimation is an important phase of software development projects. Estimation results are notoriously known for their inaccuracy. Numerous research studies tackled the problem, leading to a wide variety of effort estimating appr... Apr 17 2015   A hybrid model through the fusion of type-2 fuzzy logic systems and extreme learning machines for modelling permeability prediction Olatunji S., Selamat A., Abdulraheem A. Information Fusion 1629-45, 2014.  Type: Article The simplest computational models in artificial intelligence are so-called single hidden-layer feed-forward neural networks. These neural networks have to be trained, but the slow learning rate of simple algorithms makes this time-cons... Feb 12 2014   Applications of pulse-coupled neural networks Ma Y., Zhan K., Wang Z., Springer Publishing Company, Incorporated, New York, NY, 2011. 260 pp.  Type: Book (978-3-642137-44-0) Pulse-coupled neural networks (PCNNs) are based on the nervous system in the eyes of humans and mammals. The book describes various models of PCNNs, and related image processing algorithms. Image processing techniques such as image fil... Aug 7 2012   Ensembles of ARTMAP-based neural networks: an experimental study Canuto A., Santos A., Vargas R. Applied Intelligence 35(1): 1-17, 2011.  Type: Article The authors performed a comprehensive study on the relationship between accuracy and diversity using an ensemble of ARTMAP neural network classifiers tested with five datasets from the University of California, Irvine (UCI) repository.... Dec 29 2011   Authentication of individuals using hand geometry biometrics: a neural network approach Faundez-Zanuy M., Elizondo D., Ferrer-Ballester M., Travieso-González C. Neural Processing Letters 26(3): 201-216, 2007.  Type: Article Many reports on the use of a multi-layer perceptron (MLP) based neural network to classify biometric data exist in the literature. The technique reported on in this paper, however, is not limited to the classifier task; ... Jan 29 2008       Display 510152550100 per page
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