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  Browse All Reviews > Computing Methodologies (I) > Pattern Recognition (I.5) > Models (I.5.1) > Neural Nets (I.5.1...)  
 
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  1-10 of 31 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, Reviews: (2 of 2)

Kasongo’s paper focuses on enhancing network security through an advanced intrusion detection system (IDS) utilizing machine learning (ML) techniques. The study implements a framework using recurrent neural network (RNN) variants: long short...

May 21 2024
  A deep learning technique for intrusion detection system using a recurrent neural networks based framework
Kasongo S. Computer Communications 199113-125, 2023.  Type: Article, Reviews: (1 of 2)

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
 
 
 
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