Abstract: Data augmentation effectively addresses the imbalanced-small sample data (ISSD) problem in hyperspectral image classification (HSIC). Although most methodologies extend features in the ...
Predicts velocity and pressure fields for various Reynolds numbers. Integrates CAE for dimensionality reduction and reconstruction. Uses LSTM to capture temporal dynamics for short-term predictions.
scVAG is an innovative framework that integrates Variational Autoencoder (VAE) and Graph Attention Autoencoder (GATE) models for enhanced analysis of single-cell gene expression data. Built upon the ...
Department of Biochemistry, University of Washington, Seattle, Washington 98195, United States Institute for Protein Design, University of Washington, Seattle, Washington 98195, United States ...
Method of Multi-Mode Sensor Data Fusion with an Adaptive Deep Coupling Convolutional Auto-Encoder ()
To address the difficulties in fusing multi-mode sensor data for complex industrial machinery, an adaptive deep coupling convolutional auto-encoder (ADCCAE) fusion method was proposed. First, the ...
Abstract: Covert faults are characterized by the performance parameters falling within the normal range, without any observable abnormalities. These types of faults pose a significant risk as they ...
In the past, linear dimensionality-reduction techniques, such as Principal Component Analysis, have been used to simplify the myoelectric control of high-dimensional prosthetic hands. Nonetheless, ...
State Key Laboratory of Oncogenes and Related Genes, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai 200030, P.R. China State Key Laboratory of Oncogenes and Related Genes, ...
When touching the surface of an object, its spatial structure translates into a vibration on the skin. The perceptual system evolved to translate this pattern into a representation that allows to ...
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