EEG Functional Connection Analysis Based on the Weight Distribution of Convolutional Neural Network by Jinglong Wu, Peiwen Huang, Tiantian Liu, Go Ritsu, Duanduan Chen, Tianyi Yan

“…In this paper, we innovatively combined the functional connection with the deep learning algorithms and analysed the matrices after the weight distribution of each layer of the convolutional neural network (CNN) to obtain the connections that play a vital role in the classification. …”
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IPACN: Information-Preserving Adaptive Convolutional Network for Remote Sensing Change Detection by Hongchao Qi, Xin Gao, Jiaqiang Lei, Fenglei Wang

“…To address these issues, we introduce Information-Preserving Adaptive Convolutional Network (IPACN). IPACN features a novel Information-Preserving Backbone (IPB), leveraging principles adapted from reversible networks to minimize feature degradation during hierarchical bi-temporal feature extraction, enhancing the preservation of fine spatial details, essential for accurate change delineation. …”
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VG-CGARN: Video Generation Using Convolutional Generative Adversarial and Recurrent Networks by Fatemeh Sobhani Manesh, Amin Nazari, Muharram Mansoorizadeh, MirHossein Dezfoulian

“…This paper proposes a novel hybrid framework that combines convolutional neural networks (CNNs), recurrent neural networks (RNNs) with long short-term memory (LSTM) units, and generative adversarial networks (GANs) to synthesize temporally consistent and spatially realistic video sequences from still images. …”
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Multistation Wind Speed Forecasting Based on Dynamic Spatiotemporal Graph Convolutional Networks by Jianhong Gan, Runqing Kang, Xun Deng, Chentao Mao, Zhibin Li, Peiyang Wei, Chunjiang Wu, Tongli He

“…We simultaneously integrate temporal- and frequency-domain convolutions to capture multiscale temporal-frequency features. …”
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Arrhythmia classification based on multi-input convolutional neural network with attention mechanism. by Bin Zheng, Wenbo Luo, Mingming Zhang, Huiyuan Jin

“…In this work, we propose a novel arrhythmia classification algorithm based on a multi-input convolutional neural network (CNN) enhanced with a Squeeze-and-Excitation (SE) attention mechanism. …”
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Diagnosis of steam turbine rotor based on improved convolutional neural network algorithm by Zhongtao Zhou, Miao Zhou, Hui Huang, Yanghai Li, Wanbing Xu

“…The data collected experimentally was used to perform a comprehensive analysis of the temporal and spectral signal characteristics. Use the obtained data to train and enhance the convolutional neural network fault diagnosis model. …”
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Photonic neuromorphic accelerator for convolutional neural networks based on an integrated reconfigurable mesh by Aris Tsirigotis, George Sarantoglou, Stavros Deligiannidis, Erica Sánchez, David Sanchez, Ana Gutierrez, Adonis Bogris, Jose Capmany, Charis Mesaritakis

“…Numerical results demonstrate that with only 7 photonic nodes, critical modules of a digital convolutional neural network can be replaced. As a result, a 98.6% accuracy on the MNIST dataset was numerically achieved, with an estimation of power consumption reduction up to 30% compared to digital convolutional neural networks. …”
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A novel Knowledge Graph recommendation algorithm based on Graph Convolutional Network by Hui Guo, Chengyong Yang, Liqing Zhou, Shiwei Wei

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Hand-aware graph convolution network for skeleton-based sign language recognition by Juan Song, Huixuechun Wang, Jianan Li, Jian Zheng, Zhifu Zhao, Qingshan Li

“…Skeleton-based sign language recognition (SLR) is a challenging research area mainly due to the fast and complex hand movement. Currently, graph convolution networks (GCNs) have been employed in skeleton-based SLR and achieved remarkable performance. …”
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Load aggregator adjustable capability forecasting based on graph convolution neural network by DONG Lingrui, WU Binyuan

“…To this end, this paper proposes a forecasting method for load aggregator based on the graph convolution neural (GCN) network. All customers are classified into several groups according to their historical load profile, and then, tailored DR models are built for each group to construct the response sample library. …”
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Reconstruction of reservoir rock using attention-based convolutional recurrent neural network by Indrajeet Kumar, Anugrah Singh

“…We propose a novel algorithm consisting of the convolutional neural network, an attention mechanism, and a recurrent neural network for the reconstruction of reservoir rock or porous media images. …”
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Temporal Enhancement of Top-N Recommendation on Heterogeneous Graphs by Feng Hu, Jun Lin

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Efficient Real-Time Sports Action Pose Estimation via EfficientPose and Temporal Graph Convolution by Yuanzhe Ma, Hui Li, Hongqiao Yan

“…This paper presents a real-time pose estimation framework that integrates EfficientPose and T-GCN (Temporal Graph Convolutional Networks) to address the challenges of dynamic and complex sports scenarios. …”
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State of Health Prediction for Lithium-Ion Batteries Based on Gated Temporal Network Assisted by Improved Grasshopper Optimization by Xiankun Wei, Silun Peng, Mingli Mo

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Advancing EEG based stress detection using spiking neural networks and convolutional spiking neural networks by Aaditya Joshi, Paramveer Singh Matharu, Lokesh Malviya, Manoj Kumar, Akshay Jadhav

“…Traditional methods often fall short in capturing the intricate temporal dynamics inherent in EEG data. This paper explores the use of Convolutional Spiking Neural Networks (CSNNs) to enhance EEG signal classification. …”
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Performance Evaluation of 3-D Convolutional Neural Network for Multitemporal Flood Classification Framework With Synthetic Aperture Radar Image Data by Dodi Sudiana, Indra Riyanto, Mia Rizkinia, Rahmat Arief, Anton Satria Prabuwono, Josaphat Tetuko Sri Sumantyo, Ketut Wikantika

Subjects: “…3-D convolutional neural network (3-D CNN)…”
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Damage detection in structural health monitoring using hybrid convolution neural network and recurrent neural network by Dung Bui-Ngoc, Hieu Nguyen-Tran, Lan Nguyen-Ngoc, Hoa Tran-Ngoc, Thanh Bui-Tien, Hung Tran-Viet

“…In this paper, a novel method of structural damage detection is proposed using a hybrid convolution neural network and recurrent neural network. …”
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Multi-Scale Building Load Forecasting Without Relying on Weather Forecast Data: A Temporal Convolutional Network, Long Short-Term Memory Network, and Self-Attention Mechanism Approach by Lanqian Yang, Jinmin Guo, Huili Tian, Min Liu, Chang Huang, Yang Cai

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Self-adaptive spatial-temporal network based on heterogeneous data for air quality prediction by Feng Chang, Liang Ge, Siyu Li, Kunyan Wu, Yaqian Wang

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Instantaneous 2D extreme wind speed prediction using the novel Wind Gust Prediction Net based on purely convolutional neural mechanism by Zeguo Zhang, Jianchuan Yin

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