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A comprehensive survey of digital twins and federated learning for industrial internet of things (IIoT), internet of vehicles (IoV) and internet of drones (IoD)
As a result of the advancement in the fourth industrial revolution and communication
technology, the use of digital twins (DT) and federated learning (FL) in the industrial Internet …
technology, the use of digital twins (DT) and federated learning (FL) in the industrial Internet …
A comprehensive survey of transformers for computer vision
As a special type of transformer, vision transformers (ViTs) can be used for various computer
vision (CV) applications. Convolutional neural networks (CNNs) have several potential …
vision (CV) applications. Convolutional neural networks (CNNs) have several potential …
DenseSPH-YOLOv5: An automated damage detection model based on DenseNet and Swin-Transformer prediction head-enabled YOLOv5 with attention mechanism
Objective. Computer vision-based up-to-date accurate damage classification and
localization are of decisive importance for infrastructure monitoring, safety, and the …
localization are of decisive importance for infrastructure monitoring, safety, and the …
WilDect-YOLO: An efficient and robust computer vision-based accurate object localization model for automated endangered wildlife detection
Objective. With climatic instability, various ecological disturbances, and human actions
threaten the existence of various endangered wildlife species. Therefore, an up-to-date …
threaten the existence of various endangered wildlife species. Therefore, an up-to-date …
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 …
imagery (MI) has emerged as a powerful method for establishing direct communication …
Deep learning-based cost-effective and responsive robot for autism treatment
Recent studies state that, for a person with autism spectrum disorder, learning and
improvement is often seen in environments where technological tools are involved. A robot …
improvement is often seen in environments where technological tools are involved. A robot …
An efficient and robust phonocardiography (pcg)-based valvular heart diseases (vhd) detection framework using vision transformer (vit)
Background and objectives: Valvular heart diseases (VHDs) are one of the dominant causes
of cardiovascular abnormalities that have been associated with high mortality rates globally …
of cardiovascular abnormalities that have been associated with high mortality rates globally …
Deep learning-accelerated computational framework based on physics informed neural network for the solution of linear elasticity
The paper presents an efficient and robust data-driven deep learning (DL) computational
framework developed for linear continuum elasticity problems. The methodology is based on …
framework developed for linear continuum elasticity problems. The methodology is based on …
A data-driven physics-constrained deep learning computational framework for solving von Mises plasticity
Current work presents an efficient data-driven Physics Informed Neural Networks (PINNs)
computational framework for the solution of elastoplastic solid mechanics. To incorporate …
computational framework for the solution of elastoplastic solid mechanics. To incorporate …
Introducing urdu digits dataset with demonstration of an efficient and robust noisy decoder-based pseudo example generator
In the present work, we propose a novel method utilizing only a decoder for generation of
pseudo-examples, which has shown great success in image classification tasks. The …
pseudo-examples, which has shown great success in image classification tasks. The …