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Use of artificial neural networks in architecture: determining the architectural style of a building with a convolutional neural networks
The discussion of "can machines think?" which started with the invention of the modern computer, brought along the question of "can machines design?"...
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Improving learning in Artificial Neural Networks using better weight initializations
Artificial Neural Networks is a popular choice in optimization tasks for a number of applications such as approximations, regression, classification....
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Pseudo datasets explain artificial neural networks
Machine learning enhances predictive ability in various research compared to conventional statistical approaches. However, the advantage of the...
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Multi-fuzzy sets and neural networks: a collaborative tool for artificial intelligence
This article proposes Multi-Fuzzy Sets and Neural Networks as a collaborative tool for generating artificial intelligence. The study illustrates the...
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COOT optimization algorithm on training artificial neural networks
In recent years, significant advancements have been made in artificial neural network models and they have been applied to a variety of real-world...
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A survey of fractional calculus applications in artificial neural networks
Artificial neural network (ANN) is the backbone of machine learning, specifically deep learning. The interpolating and learning ability of an ANN...
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A new deep neural network for forecasting: Deep dendritic artificial neural network
Deep artificial neural networks have become a good alternative to classical forecasting methods in solving forecasting problems. Popular deep neural...
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Artificial Neural Networks
Artificial neural networks (ANN) surely brought a noticeable evolution to the AI field. A data scientist has now a choice between the two...
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Optimization of Artificial Neural Networks using Wavelet Transforms
AbstractThe article presents the artificial neural networks performance optimization using wavelet transform. The existing approaches of wavelet...
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Artificial Neural Networks
Artificial Neural Networks (ANNs) are computational methods that belong to the field of Machine Learning [Mitchell, 1997, Kelleher et al., 2015,...
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Artificial glial cells in artificial neuronal networks: a systematic review
The concept of tripartite synapses has revolutionized the world of neuroscience and the way we understand how information is transmitted in the...
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Artificial Neural Networks in Pattern Recognition 10th IAPR TC3 Workshop, ANNPR 2022, Dubai, United Arab Emirates, November 24–26, 2022, Proceedings
This book constitutes the refereed proceedings of the 10th IAPR TC3 International Workshop on Artificial Neural Networks in Pattern Recognition,...
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Deep Learning and Artificial Neural Networks
In this chapter, we delve into the world of applied deep learning and artificial neural networks. Our primary focus will be on their application in...
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Investigation of factors affecting transactional distance in E-learning environment with artificial neural networks
In this study, the factors affecting the transactional distance levels of university students who continue their courses with distance education in...
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Method for the Adaptive Neutralization of Structural Breaches in Cyber-Physical Systems Based on Graph Artificial Neural Networks
AbstractThis paper presents a model of threats in cyber-physical systems (CPSs) with examples of attacks and potential negative consequences for...
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Chord-based music generation using long short-term memory neural networks in the context of artificial intelligence
With the rapid development of artificial intelligence (AI), music generation has gained widespread attention. Long short-term memory (LSTM) has...
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Investigating the usability of a new framework for creating, working and teaching artificial neural networks using augmented reality (AR) and virtual reality (VR) tools
Deep learning is a very popular topic in computer sciences courses despite the fact that it is often challenging for beginners to take their first...
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MLDC: multi-lung disease classification using quantum classifier and artificial neural networks
Lung diseases are one of the most common diseases around the world. The risk of these diseases are more in under-developed and develo** countries,...
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Laplace based Bayesian inference for ordinary differential equation models using regularized artificial neural networks
Parameter estimation and associated uncertainty quantification is an important problem in dynamical systems characterised by ordinary differential...
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Rainfall forecasting at long lead times for eastern Australia using artificial neural networks
Forecasting using artificial neural networks (ANNs) has previously been demonstrated to provide skilful monthly and seasonal rainfall forecasts for...
