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Application of Transformer Models to Landslide Susceptibility Mapping.

Sensors (Basel, Switzerland)
Landslide susceptibility mapping (LSM) is of great significance for the identification and prevention of geological hazards. LSM is based on convolutional neural networks (CNNs); CNNs use fixed convolutional kernels, focus more on local information a...

Towards Online Ageing Detection in Transformer Oil: A Review.

Sensors (Basel, Switzerland)
Transformers play an essential role in power networks, ensuring that generated power gets to consumers at the safest voltage level. However, they are prone to insulation failure from ageing, which has fatal and economic consequences if left undetecte...

Smartphone Sensor-Based Human Motion Characterization with Neural Stochastic Differential Equations and Transformer Model.

Sensors (Basel, Switzerland)
With many conveniences afforded by advances in smartphone technology, developing advanced data analysis methods for health-related information from smartphone users has become a fast-growing research topic in the healthcare field. Along these lines, ...

ConvWin-UNet: UNet-like hierarchical vision Transformer combined with convolution for medical image segmentation.

Mathematical biosciences and engineering : MBE
Convolutional Neural Network (CNN) plays a vital role in the development of computer vision applications. The depth neural network composed of U-shaped structures and jump connections is widely used in various medical image tasks. Recently, based on ...

Adversarial attacks and adversarial robustness in computational pathology.

Nature communications
Artificial Intelligence (AI) can support diagnostic workflows in oncology by aiding diagnosis and providing biomarkers directly from routine pathology slides. However, AI applications are vulnerable to adversarial attacks. Hence, it is essential to q...

Intelligent Detection and Diagnosis of Power Failure Relying on BP Neural Network Algorithm.

Computational intelligence and neuroscience
The development of economy and the needs of urban planning have led to the rapid growth of power applications and the corresponding frequent occurrence of power failures, which many times lead to a series of economic losses due to failure to repair i...

Deep learning based optimal energy management for photovoltaic and battery energy storage integrated home micro-grid system.

Scientific reports
The development of the advanced metering infrastructure (AMI) and the application of artificial intelligence (AI) enable electrical systems to actively engage in smart grid systems. Smart homes with energy storage systems (ESS) and renewable energy s...

A Robust Visual Tracking Method Based on Reconstruction Patch Transformer Tracking.

Sensors (Basel, Switzerland)
Recently, the transformer model has progressed from the field of visual classification to target tracking. Its primary method replaces the cross-correlation operation in the Siamese tracker. The backbone of the network is still a convolutional neural...

End-to-End Point Cloud Completion Network with Attention Mechanism.

Sensors (Basel, Switzerland)
We propose a conceptually simple, general framework and end-to-end approach to point cloud completion, entitled PCA-Net. This approach differs from the existing methods in that it does not require a "simple" network, such as multilayer perceptrons (M...

Transfer learning based generalized framework for state of health estimation of Li-ion cells.

Scientific reports
Estimating the state of health (SOH) of batteries powering electronic devices in real-time while in use is a necessity. The applicability of most of the existing methods is limited to the datasets that are used to train the models. In this work, we p...