Search Results - "Tu, Jingzhi"

SWCGAN: Generative Adversarial Network Combining Swin Transformer and CNN for Remote Sensing Image Super-Resolution by Tu, Jingzhi, Mei, Gang, Ma, Zhengjing, Piccialli, Francesco

“…Easy and efficient acquisition of high-resolution remote sensing images is of importance in geographic information systems. Previously, deep neural networks…”
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An improved Nyström spectral graph clustering using k-core decomposition as a sampling strategy for large networks by Tu, Jingzhi, Mei, Gang, Piccialli, Francesco

“…Clustering on graphs (networks) is becoming intractable due to increasing sizes. Nyström spectral graph clustering (NSC) is a popular method to circumvent the…”
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Numerical Investigation of Progressive Slope Failure Induced by Sublevel Caving Mining Using the Finite Difference Method and Adaptive Local Remeshing by Tu, Jingzhi, Zhang, Yanlin, Mei, Gang, Xu, Nengxiong

“…Slope failure induced by sublevel caving mining is a progressive process, resulting in the large deformation and displacement of rock masses in the slope…”
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Comparative investigation of parallel spatial interpolation algorithms for building large-scale digital elevation models by Tu, Jingzhi, Yang, Guoxiang, Qi, Pian, Ding, Zengyu, Mei, Gang

“…The building of large-scale Digital Elevation Models (DEMs) using various interpolation algorithms is one of the key issues in geographic information science…”
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A Deep Learning Approach for Long-Term Traffic Flow Prediction With Multifactor Fusion Using Spatiotemporal Graph Convolutional Network by Qi, Xiaoyu, Mei, Gang, Tu, Jingzhi, Xi, Ning, Piccialli, Francesco

“…As a vital research subject in the field of intelligent transportation systems (ITSs), traffic flow prediction using deep learning methods has attracted much…”
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Physics-Informed Neural Network Integrating PointNet-Based Adaptive Refinement for Investigating Crack Propagation in Industrial Applications by Tu, Jingzhi, Liu, Chun, Qi, Pian

“…Crack is one of the critical factors that degrade the performance of machinery manufacturing equipment. Recently, physics-informed neural networks (PINNs) have…”
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An Efficient Deep Learning Approach Using Improved Generative Adversarial Networks for Incomplete Information Completion of Self-driving Vehicles by Tu, Jingzhi, Mei, Gang, Piccialli, Francesco

“…Autonomous driving is a key technology for intelligent logistics in the Industrial Internet of Things (IIoT). In autonomous driving, the appearance of…”
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An efficient graph clustering algorithm by exploiting k-core decomposition and motifs by Mei, Gang, Tu, Jingzhi, Xiao, Lei, Piccialli, Francesco

“…Clustering analysis has been widely used in trust evaluation for various complex networks such as wireless sensor networks and online social networks. Spectral…”
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Julia language in machine learning: Algorithms, applications, and open issues by Gao, Kaifeng, Mei, Gang, Piccialli, Francesco, Cuomo, Salvatore, Tu, Jingzhi, Huo, Zenan

“…Machine learning is driving development across many fields in science and engineering. A simple and efficient programming language could accelerate…”
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An Efficient Deep Learning Approach Using Improved Generative Adversarial Networks for Incomplete Information Completion of Self-driving by Tu, Jingzhi, Mei, Gang, Piccialli, Francesco

“…Autonomous driving is the key technology of intelligent logistics in Industrial Internet of Things (IIoT). In autonomous driving, the appearance of incomplete…”
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Research on Blind Source Separation of Mechanical Fault Based on LMD-VbHMM by Yuan, Jin, Li, Zhinong, Tu, Jingzhi

“…Combining the advantages of local mean decomposition and variational Bayesian hidden Markov model, a blind source separation method for mechanical faults based…”
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Mechanical Fault Diagnosis Based on Variational Bayesian Hidden Markov Model by Zhang, Xiqin, Li, Zhinong, Tu, Jingzhi

“…In order to overcome the deficiency in the traditional static independent component analysis(ICA) source separation, i.e. the traditional static independent…”
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KCoreMotif: An Efficient Graph Clustering Algorithm for Large Networks by Exploiting k-core Decomposition and Motifs by Mei, Gang, Tu, Jingzhi, Xiao, Lei, Piccialli, Francesco

“…Computers & Electrical Engineering, 2021 Clustering analysis has been widely used in trust evaluation on various complex networks such as wireless sensors…”
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Julia Language in Machine Learning: Algorithms, Applications, and Open Issues by Gao, Kaifeng, Mei, Gang, Piccialli, Francesco, Cuomo, Salvatore, Tu, Jingzhi, Huo, Zenan

“…Computer Science Review, Volume 37, 2020, 100254 Machine learning is driving development across many fields in science and engineering. A simple and efficient…”
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Research on Estimation Method of Mechanical Fault Source Number Based on VbHMM by ZHU, Yajing, LI, Zhinong, TU, Jingzhi

“…The traditional source number estimation method must ensure that the signal sources are independent and noise-free interference. Based on the above deficiency…”
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