Search for the optimal smoothing method to improve S/N in cosmic maser spectra by Egliene Anete, Aberfelds Artis

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Acoustic emission localization model of concrete material based on convolutional neural network by DENG Yongdong, ZHOU Jingren, LU Xiang, CHEN Jiangkang

“…In this paper, a convolutional neural network-based acoustic emission localization model is constructed by taking the cylindrical concrete specimen as the experimental object, taking the 3D coordinates of eight sensors and the propagation time difference as input, and the 3D coordinate position of the acoustic emission source as output. …”
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Reservoir Stochastic Simulation Based on Octave Convolution and Multistage Generative Adversarial Network by Xuechao Wu, Wenyao Fan, Shijie Peng, Bing Qin, Qing Wang, Mingjie Li, Yang Li

“…Specifically, a pyramid structure is introduced to perform multiscale representation based on single Training Image (TI), with feature information being captured under different scales. Then, the octave convolution is used to perform multi-frequency feature representation on different feature maps. …”
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Deep spatio-temporal dependent convolutional LSTM network for traffic flow prediction by Jie Tang, Rong Zhu, Fengyun Wu, Xuansen He, Jing Huang, Xianlai Zhou, Yishuai Sun

“…In this paper, we design a space-dependent attention mechanism, which assigns a convolutional neural network with a different kernel size to each region through attention weights. …”
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Criminal emotion detection framework using convolutional neural network for public safety by Jay Raval, Nilesh Kumar Jadav, Sudeep Tanwar, Giovanni Pau, Fayez Alqahtani, Amr Tolba

“…Once the crime is detected, criminal faces are extracted using the region of interest and stored in a directory. Different CNN architectures, such as LeNet-5, VGGNet, RestNet-50, and basic CNN, are used to detect different emotions of the face. …”
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AFMF: adaptive fusion of multi-hop neighborhood features in graph convolutional network by Kang Liu, Xinyu Li, Lian Liu, Zhihao Xv, Aohang Pei, Runshi Ji

“…However, heterophilic graphs where adjacent nodes may belong to different categories are ubiquitous and cannot be directly processed by GNNs. …”
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Model Predictive Control Algorithm for Converter Based on a Convolutional Neural Network by Kun Shen, Mengyao Wu, Rongbin Chen

“…However, the limited generalization capability of neural network controllers leads to degraded control performance when converter load types vary, so it is essential to design switching rules for neural network controller model parameters tailored to different load types and rapidly identify the converter load type. …”
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Fusion of Geochemical Data and Remote Sensing Data Based on Convolutional Neural Network by Shi Bai, Jie Zhao, Tianhan Yu, Yunqing Shao

“…And transfer learning is applied to the fusion of different elements. Ag and Cr are selected to verify the mobility and generalization of the model. …”
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Through-Wall Radar Classification of Human Posture Using Convolutional Neural Networks by Alper Kılıç, İsmail Babaoğlu, Ahmet Babalık, Ahmet Arslan

“…On the other hand, the success of classification with deep learning methods in different problems is remarkable. Since the radar signals contain valuable information about the objects behind the wall, the use of deep learning techniques for classification purposes will give a different direction to the research. …”
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Research on basketball footwork recognition based on a convolutional neural network algorithm by Weili Bao, Yong Bai

“…Results: The experimental results showed that the acceleration and angular velocity signals of different basketball footwork had distinct differences. …”
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A Dual-channel Progressive Graph Convolutional Network via subgraph sampling by Wenrui Guan, Xun Wang

“…Graph Convolutional Networks (GCNs) demonstrate an excellent performance in node classification tasks by updating node representation via aggregating information from the neighbor nodes. …”
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Arsitektur Convolutional Neural Network untuk Model Klasifikasi Citra Batik Yogyakarta by Arya Prayoga, Maimunah, Pristi Sukmasetya, Muhammad Resa Arif Yudianto, Rofi Abul Hasani

“…The recognition of Yogyakarta batik motifs can utilize technology to classify images of Yogyakarta batik motifs based on patterns using the Convolutional Neural Network (CNN). The Yogyakarta batik motif images used for classification totaled 600 images consisting of 3 different motifs such as ceplok, kawung, and parang. …”
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Convolutional Neural Networks to Facilitate the Continuous Recognition of Arabic Speech with Independent Speakers by Sally A. Sayed, Rania Ahmed Abdel Azeem Abul Seoud, Howida Y. Abdel Naby

“…The first uses a combination of convolutional neural network (CNN) and long short-term memory (LSTM) encoders, and an attention-based decoder, and the second is based on the Sphinx-4 recognizer, which includes pocket sphinx, base sphinx, and sphinx train, with various types and number of features to be extracted (filter bank and mel frequency cepstral coefficients (MFCC)) based on the CMU Sphinx tool, which generates a language model for different sentences spoken by different speakers. …”
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Load aggregator adjustable capability forecasting based on graph convolution neural network by DONG Lingrui, WU Binyuan

“…An undirected graph is established, whose nodes are different clusters, edges are the response characteristics correlation among clusters, and node characteristic matrix is the response characteristics of each cluster. …”
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Spatio-temporal transformer and graph convolutional networks based traffic flow prediction by Jin Zhang, Yimin Yang, Xiaoheng Wu, Sen Li

“…In the spatial dimension, the model incorporates a spatial embedding module and a multi-graph convolutional module. The former is designed to learn traffic characteristics of different nodes, and the latter is used to extract spatial correlations effectively from multiple graphs. …”
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Learning super-resolution and pyramidal convolution residual network for vehicle re-identification by Mengxue Liu, Weidong Min, Qing Han, Hongyue Xiang, Meng Zhu

“…Then, multi levels of pyramidal convolution operations are designed to generate multi-scale features, which can capture information on different scales. …”
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Novel similarity calculation method of multisource ontology based on graph convolution network by Liuqian SUN, Yuliang WEI, Bailing WANG

“…In the information age, the amount of data is growing exponentially.However, different data sources are heterogeneous, which makes it inconvenient to share and multiplex data.With the rapid development of semantic network, ontology mapping is an effective method to solve this problem.The core of ontology mapping is ontology similarity calculation.Therefore, a calculation method based on graph convolution network was proposed.Firstly, ontologiesare modeled as a heterogeneous graph network, then the graph convolution network was used to learn the text embedding rules, which made ontologies were definedin global unified representation.Lastly, multisource data fusion was completed.The experimental results show that the accuracy of the proposed method is higher than other methods, and the accuracy of multi-source data fusion was effectively improved.…”
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DDoS Attacks Detection With Deep Learning Approach Using Convolutional Neural Network by Rafiq Amalul Widodo, Mera Kartika Delimayanti, Asri Wulandari

“…The model demonstrates promising performance in detecting different network traffic anomalies, offering significant insight into its potential for practical use. …”
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Voice activity detection in noisy conditions using tiny convolutional neural network by R. S. Vashkevich, E. S. Azarov

“…An extremely compact convolutional neural network is proposed. The model has only 385 trainable parameters. …”
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Applications of Convolutional Neural Network for Classification of Land Cover and Groundwater Potentiality Zones by Asnakew Mulualem Tegegne

“…In the field of groundwater engineering, a convolutional neural network (CNN) has become a great role to assess the spatial groundwater potentiality zones and land use/land cover changes based on remote sensing (RS) technology. …”
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