Lightweight pose estimation spatial-temporal enhanced graph convolutional model for miner behavior recognition by WANG Jianfang, DUAN Siyuan, PAN Hongguang, JING Ningbo

“…To address this issue, this study proposed a miner behavior recognition model based on a lightweight pose estimation network (Lite-HRNet) and a multi-dimensional feature-enhanced spatial-temporal graph convolutional network (MEST-GCN). …”
Get full text

Lifetime Prediction Analysis of Proton Exchange Membrane Fuel Cells Based on Empirical Mode Decomposition—Temporal Convolutional Network by Chao Zheng, Changqing Du, Jiaming Zhang, Yiming Zhang, Jun Shen, Jiaxin Huang

“…This study proposes a novel EMD-TCN-GN algorithm, which, for the first time, integrates empirical mode decomposition (EMD), temporal convolutional network (TCN), and group normalization (GN) by using EMD to adaptively decompose non-stationary signals (such as voltage fluctuations), the dilated convolution of TCN to capture long-term dependencies, and combining GN to group-calibrate intrinsic mode function (IMF) features to solve the problems of modal aliasing and training instability. …”
Get full text

Multipath Effects Mitigation in Offshore Construction Platform GNSS-RTK Displacement Monitoring Using Parametric Temporal Convolution Network by Yiyang Jiang, Cheng Guo, Jinfeng Wang, Rongqiao Xu

Subjects: Get full text

On Traffic Prediction With Knowledge-Driven Spatial–Temporal Graph Convolutional Network Aided by Selected Attention Mechanism by Yuwen Qian, Tianyang Qiu, Chuan Ma, Yiyang Ni, Long Yuan, Xiangwei Zhou, Jun Li

“…In this paper, we propose the knowledge-driven graph convolutional network (KGCN) aided by the gated recurrent unit with a selected attention mechanism (GSAM) to predict traffic flow. …”
Get full text

Fault detection and classification in overhead transmission lines through comprehensive feature extraction using temporal convolution neural network by Nadeem Ahmed Tunio, Ashfaque Ahmed Hashmani, Suhail Khokhar, Mohsin Ali Tunio, Muhammad Faheem

Subjects: Get full text

Examining the complex and cumulative effects of environmental exposures on noise perception through interpretable spatio-temporal graph convolutional networks by Liuyi Song, Mei-Po Kwan, Yang Liu

“…To address this gap, this study employs noise exposure as a case study and utilizes an interpretable spatio-temporal graph convolutional network (ST-GCN) framework to model the perception process in urban environments. …”
Get full text

Fusion of Multimodal Spatio-Temporal Features and 3D Deformable Convolution Based on Sign Language Recognition in Sensor Networks by Qian Zhou, Hui Li, Weizhi Meng, Hua Dai, Tianyu Zhou, Guineng Zheng

Subjects: Get full text

Design of mTCN framework for disaster prediction a fusion of massive machine type communications and temporal convolutional networks by M. Umadevi, J. Arun Kumar, S. Vishnu Priyan, C. Vivek

Subjects: Get full text

A framework for continual learning in real-time traffic forecasting utilizing spatial–temporal graph convolutional recurrent networks by Mariam Labib Francies, Abeer Twakol Khalil, Hanan M. Amer, Mohamed Maher Ata

“…Although Deep Learning (DL) models demonstrate potential, their significant computational requirements and susceptibility to catastrophic forgetting limit their effectiveness in dynamic and real-time contexts, including traffic emergencies or evolving road networks. To address these challenges, this research presents an innovative framework known as the Continual Learning-based Spatial–Temporal Graph Convolutional Recurrent Neural Network (STGNN-CL) for persistent and accurate long-term traffic flow prediction. …”
Get full text

Voice-AttentionNet: Voice-Based Multi-Disease Detection with Lightweight Attention-Based Temporal Convolutional Neural Network by Jintao Wang, Jianhang Zhou, Bob Zhang

Subjects: Get full text

Solar Cycle Prediction Using a Temporal Convolutional Network Deep-learning Model with a One-step Pattern by Cui Zhao, Kun Liu, Shangbin Yang, Jinchao Xia, Jingxia Chen, Jie Ren, Shiyuan Liu, Fangyuan He

“…In this paper a solar cycle prediction method based on a one-step pattern is proposed with the temporal convolutional network neural network model, in which historical data are input and only one value is predicted at a time. …”
Get full text

A New Frontier in Wind Shear Intensity Forecasting: Stacked Temporal Convolutional Networks and Tree-Based Models Framework by Afaq Khattak, Jianping Zhang, Pak-wai Chan, Feng Chen, Abdulrazak H. Almaliki

Subjects: Get full text

Fully convolutional video prediction network for complex scenarios by Rui Han, Shuaiwei Liang, Fan Yang, Yong Yang, Chen Li

Get full text

An Ensemble of Convolutional Neural Networks for Sound Event Detection by Abdinabi Mukhamadiyev, Ilyos Khujayarov, Dilorom Nabieva, Jinsoo Cho

“…This research presents a comprehensive study of an ensemble convolutional recurrent neural network (CRNN) model designed for sound event detection (SED) in residential and public safety contexts. …”
Get full text

Automated Cough Analysis with Convolutional Recurrent Neural Network by Yiping Wang, Mustafaa Wahab, Tianqi Hong, Kyle Molinari, Gail M. Gauvreau, Ruth P. Cusack, Zhen Gao, Imran Satia, Qiyin Fang

Get full text

Adaptive Hierarchical Multi-Headed Convolutional Neural Network With Modified Convolutional Block Attention for Aerial Forest Fire Detection by Md. Najmul Mowla, Davood Asadi, Shamsul Masum, Khaled Rabie

“…Effective detection and classification of forest fire imagery are critical for timely and efficient wildfire management. Convolutional Neural Networks (CNNs) have demonstrated potential in this domain but encounter limitations when addressing varying scales, resolutions, and complex spatial dependencies inherent in wildfire datasets. …”
Get full text

Research on Multi-Scale Spatio-Temporal Graph Convolutional Human Behavior Recognition Method Incorporating Multi-Granularity Features by Yulin Wang, Tao Song, Yichen Yang, Zheng Hong

“…Finally, an end-to-end graph convolutional neural network is constructed to improve the feature expression ability of spatio-temporal receptive field information and enhance the robustness of recognition between similar behaviors. …”
Get full text

Temporal Graph Attention Network for Spatio-Temporal Feature Extraction in Research Topic Trend Prediction by Zhan Guo, Mingxin Lu, Jin Han

“…In this model, a temporal convolutional layer is employed to extract temporal trend features from multivariate topic time series. …”
Get full text

LSTA-CNN: A Lightweight Spatiotemporal Attention-Based Convolutional Neural Network for ASD Diagnosis Using EEG by Jing Li, Xiangwei Jia, Xinghan Chen, Gongfa Li, Gaoxiang Ouyang

“…However, as a kind of neural electrophysiological signal, EEG contains different types of temporal and spatial information. Therefore, we propose a lightweight spatio-temporal attention-based convolutional neural network (LSTA-CNN) for ASD diagnosis based on EEG recordings. …”
Get full text

Learning temporal granularity with quadruplet networks for temporal knowledge graph completion by Rushan Geng, Cuicui Luo

Subjects: Get full text