Deep learning in aircraft design, dynamics, and control: Review and prospects
In recent decades, deep learning (DL) has become a rapidly growing research direction,
redefining the state-of-the-art performances in a wide range of techniques, such as object …
redefining the state-of-the-art performances in a wide range of techniques, such as object …
[HTML][HTML] Designing a grey wolf optimization based hyper-parameter optimized convolutional neural network classifier for skin cancer detection
Abstract In recent history, Convolutional Neural Networks have attained breakthroughs in
addressing many intractable problems in the domain of image processing. But its …
addressing many intractable problems in the domain of image processing. But its …
Deep learning in air traffic management (ATM): a survey on applications, opportunities, and open challenges
EC Pinto Neto, DM Baum, JR Almeida Jr… - Aerospace, 2023 - mdpi.com
Currently, the increasing number of daily flights emphasizes the importance of air
transportation. Furthermore, Air Traffic Management (ATM) enables air carriers to operate …
transportation. Furthermore, Air Traffic Management (ATM) enables air carriers to operate …
A new end-to-end multi-dimensional CNN framework for land cover/land use change detection in multi-source remote sensing datasets
ST Seydi, M Hasanlou, M Amani - Remote Sensing, 2020 - mdpi.com
The diversity of change detection (CD) methods and the limitations in generalizing these
techniques using different types of remote sensing datasets over various study areas have …
techniques using different types of remote sensing datasets over various study areas have …
[HTML][HTML] Automatic COVID-19 disease diagnosis using 1D convolutional neural network and augmentation with human respiratory sound based on parameters: cough …
The issue in respiratory sound classification has attained good attention from the clinical
scientists and medical researcher's group in the last year to diagnosing COVID-19 disease …
scientists and medical researcher's group in the last year to diagnosing COVID-19 disease …
Prediction of the remaining useful life of cutting tool using the Hurst exponent and CNN-LSTM
To enhance production quality, productivity and energy consumption, it is paramount to
predict the remaining useful life (RUL) of a cutting tool accurately and efficiently. Deep …
predict the remaining useful life (RUL) of a cutting tool accurately and efficiently. Deep …
Seamless integration of convolutional and back-propagation neural networks for regional multi-step-ahead PM2. 5 forecasting
PY Kow, YS Wang, Y Zhou, IF Kao, M Issermann… - Journal of Cleaner …, 2020 - Elsevier
The fine particulate matter (eg PM 2.5) gains an increasing concern of human health
deterioration. Modelling PM 2.5 concentrations remains a substantial challenge due to the …
deterioration. Modelling PM 2.5 concentrations remains a substantial challenge due to the …
Real-time image-based air quality estimation by deep learning neural networks
Air quality profoundly impacts public health and environmental equity. Efficient and
inexpensive air quality monitoring instruments could be greatly beneficial for human health …
inexpensive air quality monitoring instruments could be greatly beneficial for human health …
Efficient CNN‐XGBoost technique for classification of power transformer internal faults against various abnormal conditions
To increase the classification accuracy of a protection scheme for power transformer, an
effective convolution neural network (CNN) extreme gradient boosting (XGBoost) …
effective convolution neural network (CNN) extreme gradient boosting (XGBoost) …
Self-adaptive salp swarm algorithm for optimization problems
In this paper, an enhanced version of the salp swarm algorithm (SSA) for global optimization
problems was developed. Two improvements have been proposed:(i) Diversification of the …
problems was developed. Two improvements have been proposed:(i) Diversification of the …