Scientific Research Publishing

Damage Detection in Simply Supported Beams Using 1D Convolutional Neural Networks with Vibration Signals ()

1 Guangzhou Railway Polytechnic, Guangzhou, China. 2 School of Intelligent Construction and Civil Engineering, Zhongyuan University of Technology, Zhengzhou, China. 3 Research Center for Wind ...
Scientific Research Publishing

Graph Neural Networks for Anomaly Detection in Cloud Infrastructure ()

Cloud infrastructure anomalies cause significant downtime and financial losses (estimated at $2.5 M/hour for major services). Traditional anomaly detection methods fail to capture complex dependencies ...
IEEE

Spatial–Spectral Graph Convolutional Network for Hyperspectral Target Detection

Abstract: Deep-learning-based hyperspectral target detection methods commonly face challenges such as insufficient target samples and inadequate use of spatial context. To address these limitations, ...
Frontiers

Multi-Scale graph wavelet convolutional network for hyperspectral image classification

Hyperspectral images (HSIs) have very high dimensionality and typically lack sufficient labeled samples, which significantly challenges their processing and analysis. These challenges contribute to ...
Frontiers

Efficient spiking convolutional neural networks accelerator with multi-structure compatibility

1 College of Electronic Science and Technology, National University of Defense Technology, Changsha, China 2 College of Electronics and Internet of Things, Chongqing Polytechnic University of ...
IEEE

Graph Convolutional Network Aggregation For Broad-Spectral Object Detection

Abstract: Object detection is a critical component in various applications, yet conventional detection architectures are typically developed on RGB or grayscale databases, limiting their effectiveness ...