A review of deep learning techniques for speech processing

A Mehrish, N Majumder, R Bharadwaj, R Mihalcea… - Information …, 2023 - Elsevier
The field of speech processing has undergone a transformative shift with the advent of deep
learning. The use of multiple processing layers has enabled the creation of models capable …

A perspective survey on deep transfer learning for fault diagnosis in industrial scenarios: Theories, applications and challenges

W Li, R Huang, J Li, Y Liao, Z Chen, G He… - … Systems and Signal …, 2022 - Elsevier
Abstract Deep Transfer Learning (DTL) is a new paradigm of machine learning, which can
not only leverage the advantages of Deep Learning (DL) in feature representation, but also …

A review of wind speed and wind power forecasting with deep neural networks

Y Wang, R Zou, F Liu, L Zhang, Q Liu - Applied Energy, 2021 - Elsevier
The use of wind power, a pollution-free and renewable form of energy, to generate electricity
has attracted increasing attention. However, intermittent electricity generation resulting from …

[HTML][HTML] An efficient deep learning model to categorize brain tumor using reconstruction and fine-tuning

MA Talukder, MM Islam, MA Uddin, A Akhter… - Expert systems with …, 2023 - Elsevier
Brain tumors are among the most fatal and devastating diseases, often resulting in
significantly reduced life expectancy. An accurate diagnosis of brain tumors is crucial to …

Deep learning framework for lithium-ion battery state of charge estimation: Recent advances and future perspectives

J Tian, C Chen, W Shen, F Sun, R **ong - Energy Storage Materials, 2023 - Elsevier
Accurate state of charge (SOC) constitutes the basis for reliable operations of lithium-ion
batteries. The deep learning technique, a game changer in many fields, has recently …

A hybrid neural network model with improved input for state of charge estimation of lithium-ion battery at low temperatures

Z Cui, L Kang, L Li, L Wang, K Wang - Renewable Energy, 2022 - Elsevier
Lithium-ion batteries have been used in all aspects of life for environmental and resource
reasons. The accurate estimation of the state of charge (SOC) ensures the proper operation …

Adaptive transfer learning-based multiscale feature fused deep convolutional neural network for EEG MI multiclassification in brain–computer interface

AM Roy - Engineering Applications of Artificial Intelligence, 2022 - Elsevier
Abstract Objective. Deep learning (DL)-based brain–computer interface (BCI) in motor
imagery (MI) has emerged as a powerful method for establishing direct communication …

A systematic review of convolutional neural network-based structural condition assessment techniques

S Sony, K Dunphy, A Sadhu, M Capretz - Engineering Structures, 2021 - Elsevier
With recent advances in non-contact sensing technology such as cameras, unmanned aerial
and ground vehicles, the structural health monitoring (SHM) community has witnessed a …

Wafer-scale integration of two-dimensional perovskite oxides towards motion recognition

M Deng, Z Li, S Liu, X Fang, L Wu - Nature Communications, 2024 - nature.com
Two-dimensional semiconductors have shown great potential for the development of
advanced intelligent optoelectronic systems. Among them, two-dimensional perovskite …

Effective IoT-based deep learning platform for online fault diagnosis of power transformers against cyberattacks and data uncertainties

M Elsisi, MQ Tran, K Mahmoud, DEA Mansour… - Measurement, 2022 - Elsevier
The distribution of the power transformers at a far distance from the electrical plants
represents the main challenge against the diagnosis of the transformer status. This paper …