Recommendation system based on deep learning methods: a systematic review and new directions
A Da'u, N Salim - Artificial Intelligence Review, 2020 - Springer
These days, many recommender systems (RS) are utilized for solving information overload
problem in areas such as e-commerce, entertainment, and social media. Although classical …
problem in areas such as e-commerce, entertainment, and social media. Although classical …
Supervised learning in spiking neural networks: A review of algorithms and evaluations
X Wang, X Lin, X Dang - Neural Networks, 2020 - Elsevier
As a new brain-inspired computational model of the artificial neural network, a spiking
neural network encodes and processes neural information through precisely timed spike …
neural network encodes and processes neural information through precisely timed spike …
[HTML][HTML] An optical neural chip for implementing complex-valued neural network
Complex-valued neural networks have many advantages over their real-valued
counterparts. Conventional digital electronic computing platforms are incapable of executing …
counterparts. Conventional digital electronic computing platforms are incapable of executing …
Non-iterative and fast deep learning: Multilayer extreme learning machines
In the past decade, deep learning techniques have powered many aspects of our daily life,
and drawn ever-increasing research interests. However, conventional deep learning …
and drawn ever-increasing research interests. However, conventional deep learning …
[HTML][HTML] Machine learning based system for managing energy efficiency of public sector as an approach towards smart cities
Energy efficiency of public sector is an important issue in the context of smart cities due to
the fact that buildings are the largest energy consumers, especially public buildings such as …
the fact that buildings are the largest energy consumers, especially public buildings such as …
Deep learning-based intrusion detection systems: a systematic review
Nowadays, the ever-increasing complication and severity of security attacks on computer
networks have inspired security researchers to incorporate different machine learning …
networks have inspired security researchers to incorporate different machine learning …
Deep learning approach for microarray cancer data classification
HS Basavegowda, G Dagnew - CAAI Transactions on …, 2020 - Wiley Online Library
Analysis of microarray data is a highly challenging problem due to the inherent complexity in
the nature of the data associated with higher dimensionality, smaller sample size …
the nature of the data associated with higher dimensionality, smaller sample size …
[HTML][HTML] Novel deep genetic ensemble of classifiers for arrhythmia detection using ECG signals
P Pławiak, UR Acharya - Neural Computing and Applications, 2020 - Springer
The heart disease is one of the most serious health problems in today's world. Over 50
million persons have cardiovascular diseases around the world. Our proposed work based …
million persons have cardiovascular diseases around the world. Our proposed work based …
Novel methodology of cardiac health recognition based on ECG signals and evolutionary-neural system
P Pławiak - Expert Systems with Applications, 2018 - Elsevier
This article presents an innovative research methodology that enables the efficient
classification of cardiac disorders (17 classes) based on ECG signal analysis and an …
classification of cardiac disorders (17 classes) based on ECG signal analysis and an …
Machine learning algorithms to predict flow condensation heat transfer coefficient in mini/micro-channel utilizing universal data
Miniature condensers utilizing mini/micro-channel has been recognized as one effective
technique for designing a compact heat rejection device. However, because of the complex …
technique for designing a compact heat rejection device. However, because of the complex …