A Convolutional Neural Network for Coastal Classification Based on ALOS and NOAA Satellite Data by Kinh Bac Dang, Van Bao Dang, Quang Thanh Bui, Van Vuong Nguyen, Thi Phuong Nga Pham, Van Liem Ngo

“…Nowadays, the integration of deep learning in remote sensing and GIS analysis can quickly classify and detect different characteristics on both land and sea. Therefore, the authors proposed the use of a convolutional neural network (ConvNet) for coastal classification based on these technologies and geomorphic profile graphs. …”
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SAR Images Change Detection Based on Attention Mechanism-Convolutional Wavelet Neural Network by Jiahui E, Lu Wang, Chunhui Zhao, P. Takis Mathiopoulos, Tomoaki Ohtsuki, Fumiyuki Adachi

“…To deal with these problems this article proposes a SAR images change detection scheme which is based upon an Attention Mechanism and Convolutional Wavelet Neural Network. First, employing Multiscale Superpixel Reconstructed Difference Image effectively enhances the edge information of the images. …”
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Fault Diagnosis for Rotating Machinery Based on Convolutional Neural Network and Empirical Mode Decomposition by Yuan Xie, Tao Zhang

“…We carried out experiments with vibration data of 52 different categories under different machine conditions to test the validity of the approach, and the results indicate it is more accurate and reliable than previous approaches.…”
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Chasing Dragons in the Dragon's Land: A Convoluted Struggle with Drugs and Deviance in Modern China by Aftab Haider, Ashraf Ali, Muhammad Zubair

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MCE-HGCN: Heterogeneous Graph Convolution Network for Analog IC Matching Constraints Extraction by Yong Zhang, Yong Yin, Ning Xu, Bowen Jia

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Accurate Arrhythmia Classification with Multi-Branch, Multi-Head Attention Temporal Convolutional Networks by Suzhao Bi, Rongjian Lu, Qiang Xu, Peiwen Zhang

“…To address these challenges, this paper proposes a method for arrhythmia classification based on a multi-branch, multi-head attention temporal convolutional network (MB-MHA-TCN). The model integrates three convolutional branch layers with different kernel sizes and dilation rates to capture features across varying temporal scales. …”
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Method for predicting cutter remaining life based on multi-scale cyclic convolutional network by Tao Li, Yinquan Yu, Chaoqiang Huang, Jinwen Yang, Yuanchang Zhong, Yong Hao

“…In the process of predicting the remaining cutter life, the deep-learning method such as convolutional neural network does not consider the time correlation of different degradation states, which directly affects the accuracy of the remaining cutter life prediction. …”
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Land-sea Clutter Classification Method Based on Multi-channel Graph Convolutional Networks by Can LI, Zengfu WANG, Xiaoxuan ZHANG, Quan PAN

“…We propose a Multi-Channel Graph Convolutional Networks (MC-GCN) for land-sea clutter classification. …”
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Selective Auditory Attention Detection Using Combined Transformer and Convolutional Graph Neural Networks by Masoud Geravanchizadeh, Amir Shaygan Asl, Sebelan Danishvar

“…Then, a family of graph convolutional layers is used to find the most active electrodes using the spatial position of electrodes. …”
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Assisting monofloral honey classification by automated pollen identification based on convolutional neural networks by José Miguel Valiente, Juan José Martín-Osuna, Ana María Peral, Isabel Escriche

“…This Ground Truth termed POLLEN24_SP, comprises 32,285 pollen/particle images (captured by an expert using optical microscopy), covering the 24 most prevalent types of pollen grains found in Spanish honeys. Twelve different pre-existing Convolutional Neural Networks (CNN) were evaluated, achieving an accuracy rate of up to 98.03 % with EfficientNetV2M. …”
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Automatic political discourse analysis with multi-scale convolutional neural networks and contextual data by Aritz Bilbao-Jayo, Aitor Almeida

“…To do so, the authors have built a discourse classifier using multi-scale convolutional neural networks in seven different languages: Spanish, Finnish, Danish, English, German, French, and Italian. …”
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The convolution-induced topology on L∞(G) and linearly dependent translates in L1(G) by G. Crombez, W. Govaerts

“…Given a locally compact Hausdorff group G, we consider on L∞(G) the τc-topology, i.e. the weak topology under all convolution operators induced by functions in L1(G). …”
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Target detection of helicopter electric power inspection based on the feature embedding convolution model. by Dakun Liu, Wei Zhou, Linzhen Zhou, Wen Guan

“…This study aims to improve the helicopter electric power inspection process by using the feature embedding convolution (FEC) model to solve the problems of small scope and poor real-time inspection. …”
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Convolutional Interval-Valued Neutrosophic Network for Intelligent Evaluation of Smart Clothing Design Choices by Fengfang Wu

“…In an attempt to address this challenge, this research article proposes a novel Neutrosophic approach that integrates Interval-Valued Neutrosophic (IVN) with Convolutional Network to build an intelligent tool for the evaluation of smart clothing design choices. …”
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Integration of unpaired single cell omics data by deep transfer graph convolutional network. by Yulong Kan, Yunjing Qi, Zhongxiao Zhang, Xikeng Liang, Weihao Wang, Shuilin Jin

“…Thus, scTGCN shows high label transfer accuracy and effectively knowledge transfer across different modalities.…”
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SL-GCNN: A Graph Convolutional Neural Network for Granular Human Motion Recognition by Yang Li, Jingyu Zhang

“…This paper presents SL-GCNN, a novel Graph Convolutional Neural Network framework specifically designed for granular skeletal motion recognition. …”
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TEA-GCN: Transformer-Enhanced Adaptive Graph Convolutional Network for Traffic Flow Forecasting by Xiaxia He, Wenhui Zhang, Xiaoyu Li, Xiaodan Zhang

“…Specifically, we design an adaptive graph convolutional module to dynamically capture implicit road dependencies at different time levels and a local-global temporal attention module to simultaneously capture long-term and short-term temporal dependencies. …”
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Perbandingan Random Forest dan Convolutional Neural Network dalam Memprediksi Peralihan Pelanggan by Dewa Adji Kusuma, Atika Ratna Dewi, Andreas Rony Wijaya

“…The limitation of this research is how to handle the two algorithms being compared. Both use different approaches, namely Supervised Learning and Deep Learning. …”
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MagNet: Automated Magnetic Mineral Grain Morphometry Using Convolutional Neural Network by Zhaowen Pei, Liao Chang, Pengfei Xue, Richard J. Harrison

“…This framework, based on a convolutional neural network, performs well in the recognition and classification of magnetofossil nanoparticles in transmission electron microscopy images after training and testing. …”
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Bearing Life Prediction Method Based on Parallel Multichannel Recurrent Convolutional Neural Network by Jianmin Zhou, Sen Gao, Jiahui Li, Wenhao Xiong

“…The back of the model is the recurrent convolution layer to model the temporal dependence relationship under different degradation features. …”
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