Advection-Free Convolutional Neural Network for Convective Rainfall Nowcasting by Jenna Ritvanen, Bent Harnist, Miguel Aldana, Terhi Makinen, Seppo Pulkkinen

“…To address this issue, we present a novel model called the Lagrangian convolutional neural network (L-CNN) that separates the growth and decay of rainfall from motion using the advection equation. …”
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Application of improved graph convolutional network for cortical surface parcellation by Jia Tan, Xiaomei Ren, Yong Chen, Xianju Yuan, Feiba Chang, Rui Yang, Chengqun Ma, Xiaoyu Chen, Miao Tian, Wei Chen, Zihong Wang

“…In this study, we propose an Attention-guided Deep Graph Convolutional network (ADGCN) for end-to-end parcellation on primitive cortical surface manifolds. …”
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Identifying T cell antigen at the atomic level with graph convolutional network by Jinhao Que, Guangfu Xue, Tao Wang, Xiyun Jin, Zuxiang Wang, Yideng Cai, Wenyi Yang, Meng Luo, Qian Ding, Jinwei Zhang, Yilin Wang, Yuexin Yang, Fenglan Pang, Yi Hui, Zheng Wei, Jun Xiong, Shouping Xu, Yi Lin, Haoxiu Sun, Pingping Wang, Zhaochun Xu, Qinghua Jiang

“…Here we propose deepAntigen, a graph convolutional network-based framework, to identify T cell antigens at the atomic level. deepAntigen achieves excellent performance both in the prediction of antigen-human leukocyte antigen (HLA) binding and antigen-T cell receptor (TCR) interactions, which can provide comprehensive guidance for identification of T cell antigens. …”
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Research on Identification Method of Transformer Windings’ Loose Vibration Spectrum Considering a Multi-Load Current Condition by Jin Fang, Xudong Deng, Yuancan Xia, Chen Wu, Yuehua Li, Xin Li, Kaixin Chen, Fan Wang, Zhanlong Zhang

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Seismic Events Prediction Using Deep Temporal Convolution Networks by Yue Geng, Lingling Su, Yunhong Jia, Ce Han

“…This paper contributes to address the problem of long-term historical dependence on seismic time series prediction with deep temporal convolution neural networks (CNN). We propose a dilated causal temporal convolution network (DCTCNN) and a CNN long short-term memory hybrid model (CNN-LSTM) to forecast seismic events. …”
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Urban Spatiotemporal Event Prediction Using Convolutional Neural Network and Road Feature Fusion Network by Yirui Jiang, Shan Zhao, Hongwei Li, Huijing Wu, Wenjie Zhu

“…The second stage extracts urban road network information using multiscale convolution and incorporates the extracted road network feature information into the CNN. …”
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Explainable AI for Alzheimer Detection: A Review of Current Methods and Applications by Fatima Hasan Saif, Mohamed Nasser Al-Andoli, Wan Mohd Yaakob Wan Bejuri

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Classification of Rolling Bearing Defects Based on the Direct Analysis of Phase Currents by Oliwia Frankiewicz, Maciej Skowron, Jeremi Jan Jarosz, Sebastien Weisse, Jerome Valire, Krzysztof Szabat

“…This paper presents a new diagnostic approach based on convolutional neural networks (CNNs) and direct analysis of current signals. …”
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UHVDC Transmission Fault Location Based on Residual Convolutional Neural Network by LI Ji, ZHANG Xueyou, ZHANG Junjie, SHI Wen, RUAN Wei, DAI Jianfeng

“…A method based on residual convolutional neural network for high-voltage direct current transmission fault location is proposed to address the issue of excessive reliance on the attenuation constant of the transmission line in traditional ultra-high voltage direct current fault distance measurement. …”
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Image-Based Iron Slag Segmentation via Graph Convolutional Networks by Wang Long, Zheng Junfeng, Yu Hong, Ding Meng, Li Jiangyun

“…The monotonous gray value of industry images, poor image quality, and nonrigid feature of iron and slag challenge the existing fully convolutional networks (FCNs). To this end, we propose a novel spatial and feature graph convolutional network (SFGCN) module. …”
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A Residual Optronic Convolutional Neural Network for SAR Target Recognition by Ziyu Gu, Zicheng Huang, Xiaotian Lu, Hongjie Zhang, Hui Kuang

“…However, huge computational costs and power consumption are challenging the development of current DL methods. Optical neural networks have recently been proposed to provide a new mode to replace artificial neural networks. …”
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Image Recognition Based on Multiscale Pooling Deep Convolution Neural Networks by Haitao Sang, Li Xiang, Shifeng Chen, Bo Chen, Li Yan

“…To achieve this, through making full use of block information of different sizes and scales in the image, a multiscale pooling deep convolution neural network model is designed in this paper. …”
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Meta-path convolution based heterogeneous graph neural network algorithm by QIN Zhilong, DENG Kun, LIU Xingyan

“…To solve this problem, a heterogeneous graph neural network algorithm based on meta-path convolution was proposed. …”
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Global Nuclear Explosion Discrimination Using a Convolutional Neural Network by Louisa Barama, Jesse Williams, Andrew V. Newman, Zhigang Peng

“…Abstract Using P‐wave seismograms, we trained a seismic source classifier using a Convolutional Neural Network. We trained for three classes: earthquake P‐wave, underground nuclear explosion (UNE) P‐wave, and noise. …”
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A point cloud segmentation network with hybrid convolution and differential channels by Xiaoyan Zhang, Yantao Bu

“…For this reason, we propose a 3D segmentation network based on hybrid convolution and differential channels. …”
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Load recognition method based on convolutional neural network and attention mechanism by ZHAO Yitao, LI Zhao, LIU Xinglong, LUO Zhao, WANG Gang, SHEN Xin

“…Aiming at the problems of poor recognition performance of traditional algorithms and difficulty in adapting to the current complex electricity environment, a NILM load recognition method integrating convolutional neural network (CNN)-self-attention mechanism is proposed from the optimization idea of enhancing the feature extraction performance of classification algorithms. …”
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Basketball teaching methods based on 3D-Convolutional neural network by Chao Huang, Xian Wu

“…Compared to algorithms such as 2d-convolutional neural network, the dual-resolution 3d-convolutional neural network had higher accuracy and smaller mean absolute error values. …”
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Convolutional neural network-assisted design and validation of terahertz metamaterial sensor by Shunrong Chen, Chunyue Zhao, Wei Wang, Songyuan Yang, Chengjiang Zhou

“…This paper proposes a convolutional neural network (CNN)-assisted method for both forward optimization and inverse design of terahertz metamaterial sensors (TMSs), addressing the limitations imposed by reliance on manual trial-and-error processes. …”
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Diffraction-Based Overlay Metrology With Optical Convolution Layer by Jinyang Li, Hung-Fei Kuo

“…Overlay is a crucial indicator of manufacturing processing between layers. Currently, diffraction-based overlay (DBO) is widely adopted in overlay metrology. …”
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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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