AI applications to medical images: From machine learning to deep learning
Purpose Artificial intelligence (AI) models are playing an increasing role in biomedical
research and healthcare services. This review focuses on challenges points to be clarified …
research and healthcare services. This review focuses on challenges points to be clarified …
A review of modularization techniques in artificial neural networks
Artificial neural networks (ANNs) have achieved significant success in tackling classical and
modern machine learning problems. As learning problems grow in scale and complexity …
modern machine learning problems. As learning problems grow in scale and complexity …
Towards highly accurate coral texture images classification using deep convolutional neural networks and data augmentation
The recognition of coral species based on underwater texture images poses a significant
difficulty for machine learning algorithms, due to the three following challenges embedded in …
difficulty for machine learning algorithms, due to the three following challenges embedded in …
Twelve-layer deep convolutional neural network with stochastic pooling for tea category classification on GPU platform
Automatic tea-category identification is an important topic in factories and supermarkets.
Traditional methods need to extract features from tea images manually, which may not be …
Traditional methods need to extract features from tea images manually, which may not be …
Designing a composite deep learning based differential protection scheme of power transformers
This paper proposes a novel differential protection scheme based on deep neural networks
(DNN). The goal is to propose a fast, reliable, and independent protection scheme in …
(DNN). The goal is to propose a fast, reliable, and independent protection scheme in …
A machine learning approach for forecasting hierarchical time series
P Mancuso, V Piccialli, AM Sudoso - Expert Systems with Applications, 2021 - Elsevier
In this paper, we propose a machine learning approach for forecasting hierarchical time
series. When dealing with hierarchical time series, apart from generating accurate forecasts …
series. When dealing with hierarchical time series, apart from generating accurate forecasts …
Instantaneous vehicle fuel consumption estimation using smartphones and recurrent neural networks
The high level of air pollution in urban areas, caused in no small extent by road transport,
requires the implementation of continuous and accurate monitoring techniques if emissions …
requires the implementation of continuous and accurate monitoring techniques if emissions …
Sound quality prediction and improving of vehicle interior noise based on deep convolutional neural networks
X Huang, H Huang, J Wu, M Yang, W Ding - Expert Systems with …, 2020 - Elsevier
Interior sound quality plays a vital role in vehicle quality assessment because it forms users'
general impressions of vehicles and influences consumers' purchase intentions. Thus …
general impressions of vehicles and influences consumers' purchase intentions. Thus …
Estimating compressive strength of concrete using deep convolutional neural networks with digital microscope images
Compressive strength is a critical indicator of concrete quality for ensuring the safety of
existing concrete structures. As an alternative to existing nondestructive testing methods …
existing concrete structures. As an alternative to existing nondestructive testing methods …
Deep learning approaches for IoV applications and services
Internet of vehicles (IoV) has become an important revolution of intelligent transportation
system (ITS). It became an emerging research area as the need for it has increased …
system (ITS). It became an emerging research area as the need for it has increased …