Search Results - "Tang, Xianghong"

An Ensemble Deep Convolutional Neural Network Model with Improved D-S Evidence Fusion for Bearing Fault Diagnosis by Li, Shaobo, Liu, Guokai, Tang, Xianghong, Lu, Jianguang, Hu, Jianjun

“…Intelligent machine health monitoring and fault diagnosis are becoming increasingly important for modern manufacturing industries. Current fault diagnosis…”
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An imbalanced learning method based on graph tran-smote for fraud detection by Wen, Jintao, Tang, Xianghong, Lu, Jianguang

“…Fraud seriously threatens individual interests and social stability, so fraud detection has attracted much attention in recent years. In scenarios such as…”
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Spatial-temporal graph neural ODE networks for skeleton-based action recognition by Pan, Longji, Lu, Jianguang, Tang, Xianghong

“…In the field of skeleton-based action recognition, accurately recognizing human actions is crucial for applications such as virtual reality and motion…”
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Identification and factor analysis of rocky desertification severity levels in large-scale karst areas based on deep learning image segmentation by Wang, Yuhao, Tang, Xianghong, Huang, Yong, Yang, Jing, Lu, Jianguang

“…[Display omitted] •Index, texture, and spectral features can improve the identification accuracy of RDSL segmentation model.•The SegGCN model can effectively…”
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Efficient and Low-Complex Signal Detection with Iterative Feedback in Wireless MIMO-OFDM Systems by Chen, Ying, Tang, Yue, Jiang, Bin, Zhao, Yinan, Bao, Jianrong, Tang, Xianghong

“…To solve error propagation and exorbitant computational complexity of signal detection in wireless multiple-input multiple-output-orthogonal frequency division…”
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Improved Frequency Domain Turbo Equalization with Expectation Propagation Interference Cancellation in Underwater Acoustic Communications by Jiang, Bin, Tang, Yue, Zhao, Yinan, Bao, Jianrong, Liu, Chao, Tang, Xianghong

“…This paper proposes an improved frequency domain turbo equalization (IFDTE) with iterative channel estimation and feedback to achieve both a good performance…”
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Research on the Rapid Diagnostic Method of Rolling Bearing Fault Based on Cloud–Edge Collaboration by Tang, Xianghong, Xu, Lei, Chen, Gongsheng

“…Recent deep-learning methods for fault diagnosis of rolling bearings need a significant amount of computing time and resources. Most of them cannot meet the…”
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Molecular subgraph representation learning based on spatial structure transformer by Zhang, Shaoguang, Lu, Jianguang, Tang, Xianghong

“…In the field of molecular biology, graph representation learning is crucial for molecular structure analysis. However, challenges arise in recognising…”
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A Novel Method for Intelligent Single Fault Detection of Bearings Using SAE and Improved D-S Evidence Theory by Lu, Jianguang, Zhang, Huan, Tang, Xianghong

“…In order to realize single fault detection (SFD) from the multi-fault coupling bearing data and further research on the multi-fault situation of bearings, this…”
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Dual convolutional network based on hypergraph and multilevel feature fusion for road extraction from high-resolution remote sensing images by Li, BoWen, Tang, XiangHong, Xiao, Rang, Lu, JianGuang, Wang, YuHao

“…ABSTRACTRoad extraction from high-resolution remote sensing images (HRSI) is confronted with the challenge that roads are occluded by other objects, including…”
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Multi‐similarity based hyperrelation network for few‐shot segmentation by Shi, Xiangwen, Cui, Zhe, Zhang, Shaobing, Cheng, Miao, He, Lian, Tang, Xianghong

“…Few‐shot semantic segmentation aims at recognizing the object regions of unseen categories with only a few annotated examples as supervision. The key to…”
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Cuproof: Range Proof with Constant Size by Deng, Cong, You, Lin, Tang, Xianghong, Hu, Gengran, Gao, Shuhong

“…Zero-Knowledge Proof is widely used in blockchains. For example, zk-SNARK is used in Zcash as its core technology to identifying transactions without the…”
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A Bearing Fault Diagnosis Method Based on Feature Selection Feedback Network and Improved D-S Evidence Fusion by Tang, Xianghong, Gu, Xin, Wang, Jiachen, He, Qiang, Zhang, Fan, Lu, Jianguang

“…Bearings running state affects the normal operation of mechanical equipment. It is of great theoretical and practical value to carry out bearing fault…”
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Stochastic Approximate Algorithms for Uncertain Constrained K-Means Problem by Lu, Jianguang, Tang, Juan, Xing, Bin, Tang, Xianghong

“…The k-means problem has been paid much attention for many applications. In this paper, we define the uncertain constrained k-means problem and propose a…”
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Detection of Salient Crowd Motion Based on Repulsive Force Network and Direction Entropy by Zhang, Xuguang, Lin, Dujun, Zheng, Juan, Tang, Xianghong, Fang, Yinfeng, Yu, Hui

“…This paper proposes a method for salient crowd motion detection based on direction entropy and a repulsive force network. This work focuses on how to…”
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Improving Bearing Fault Diagnosis Using Maximum Information Coefficient Based Feature Selection by Tang, Xianghong, Wang, Jiachen, Lu, Jianguang, Liu, Guokai, Chen, Jiadui

“…Effective feature selection can help improve the classification performance in bearing fault diagnosis. This paper proposes a novel feature selection method…”
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Optimized Polar Coded Selective Relay Cooperation With Iterative Threshold Decision of Pseudo Posterior Probability by Jiang, Bin, Yang, Shunfeng, Bao, Jianrong, Liu, Chao, Tang, Xianghong, Zhu, Fang

“…This paper proposes an optimized polar coded selective relay cooperation with an iterative threshold decision of pseudo posterior probability to solve the…”
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Two-stage GNN-based fraud detection with camouflage identification and enhanced semantics aggregation by Zhang, Jun, Lu, Jianguang, Tang, Xianghong

“…Graph neural network (GNN) has got lots of attention recently in the fraud detection task due to its message-passing mechanism, which can aggregate neighbors…”
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Subgraph autoencoder with bridge nodes by Qin, Denggao, Tang, Xianghong, Huang, Yong, Lu, Jianguang

“…Subgraph representation learning is a burgeoning field within graph representation learning. However, current methods in this field face several issues,…”
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Subgraph representation learning with self-attention and free adversarial training by Qin, Denggao, Tang, Xianghong, Lu, Jianguang

“…Due to its capacity to capture subgraph information within graph data, subgraph representation learning has garnered considerable attention in recent years…”
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