Triple Graph Convolutional Network for Hyperspectral Image Feature Fusion and Classification by Maryam Imani, Daniele Cerra

“…In the case of hyperspectral images having high variability in spectral features, considering an image region as a graph node may degrade the class discrimination ability of networks for pixel-based classification. …”
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Research on Identification of Soft-Fault Level in VRF System Based on Classifier Chain by He Yuxuan, Shi Jingfeng, Zhou Zhenxin, Chen Huanxin, Ren Zhaoting, Xia Xingxiang, Cheng Hengda

Subjects: “…variable refrigerant flow…”
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CLASSIFICATION OF ARRHYTHMIA DISEASES BY THE CONVOLUTIONAL NEURAL NETWORK METHOD BASED ON ECG IMAGES by Agustian Arditya Pratama, Agus Maman Abadi

“…This research aimed to know the performance of the Convolutional Neural Network method in classifying arrhythmia diseases based on ECG signal images. …”
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Fault prediction of smart meter based on spatio-temporal convolution neural network by Gao Wenjun, Xue Binbin, Pang Zhenjiang

“…A fault prediction method based on spatio-temporal convolutional neural network(ST-CNN) is proposed. Firstly, the sliding window is used to integrate the time information into the characteristic variables, and the input matrix with space-time characteristics is constructed. …”
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A novel Knowledge Graph recommendation algorithm based on Graph Convolutional Network by Hui Guo, Chengyong Yang, Liqing Zhou, Shiwei Wei

“…By taking into account the temporal variable, it is possible to organise well-structured external information to connect users and items, thereby expanding user preferences to a certain extent. …”
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An Efficient 3D Model Retrieval Method Based on Convolutional Neural Network by Bo Ding, Lei Tang, Yong-jun He

“…In the index building stage, 3D models in library are projected to generate a large number of views, and then representative views are selected and input into a well-learned convolutional neural network (CNN) to extract features. …”
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Recognition of prokaryotic and eukaryotic promoters using convolutional deep learning neural networks. by Ramzan Kh Umarov, Victor V Solovyev

“…Accurate computational identification of promoters remains a challenge as these key DNA regulatory regions have variable structures composed of functional motifs that provide gene-specific initiation of transcription. …”
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Model Predictive Control Algorithm for Converter Based on a Convolutional Neural Network by Kun Shen, Mengyao Wu, Rongbin Chen

“…In the finite control set model predictive control (FCSMPC) algorithm for a converter based on a neural network, the optimal control variables computed by neural network controllers achieve decoupling between the optimal FCSMPC algorithm design and online computational burden. …”
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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

“…Therefore, based on Generative Adversarial Networks (GANs), spatial distribution patterns of regional variables can be reproduced through high-order statistical fitting. …”
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Multi-scale convolutional transformer network for motor imagery brain-computer interface by Wei Zhao, Baocan Zhang, Haifeng Zhou, Dezhi Wei, Chenxi Huang, Quan Lan

“…However, traditional CNN-based methods face challenges such as individual variability in EEG signals and the limited receptive fields of CNNs. …”
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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

“…While deep learning has advanced automated ECG analysis, challenges remain in accurately classifying arrhythmias due to signal variability, data imbalance, and feature representation limitations. …”
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Offline Signature Biometric Verification with Length Normalization using Convolution Neural Network by Zahraa Mazin Alkattan, Ghada Mohammad Tahir Aldabagh

“…This is referred to as intra-user variability. This research aims to improve the recognition accuracy of the offline signature. …”
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Integration of Convolutional Neural Network and Image Processing for Pulp Fibril Detection and Measurement by Tanachot Chirakitsakul, Pakaket Wattuya, Phichit Somboon, Panthira Jansakra, Chakrit Watcharopas

“…The proposed method leverages the discriminative capabilities of convolutional neural networks (CNNs) with adaptive image processing techniques to overcome key challenges such as low contrast, image noise, and variability in fibril morphology. …”
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Reconstruction of reservoir rock using attention-based convolutional recurrent neural network by Indrajeet Kumar, Anugrah Singh

“…The attention-based convolutional recurrent neural network (ACRNN) can reconstruct a representative sample of reservoir rocks. …”
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The Detection and Classification of Scaphoid Fractures in Radiograph by Using a Convolutional Neural Network by Tai-Hua Yang, Yung-Nien Sun, Rong-Shiang Li, Ming-Huwi Horng

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Automatic melanoma detection using an optimized five-stream convolutional neural network by Vida Esmaeili, Mahmood Mohassel Feghhi, Hadi Seyedarabi

“…For this reason, these convolutional neural networks (CNNs) cannot perceive the changed or rotated image samples as similar. …”
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The Time–Fractional Wave Equation with Variable Coefficients by Chenkuan Li

“…In this paper, we primarily use the inverse operator method to find a unique series solution to a time–fractional wave equation with variable coefficients based on the Mittag–Leffler function. …”
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Hydrogen reaction rate modeling based on convolutional neural network for large eddy simulation by Quentin Malé, Corentin J. Lapeyre, Nicolas Noiray

“…Our data-driven approach leverages a Convolutional Neural Network (CNN), trained to approximate filtered burning rates from emulated LES data. …”
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Color image hybrid noise filtering algorithm based on deep convolution neural network by Yongfei Yu, Yuanjian Yan

“…To solve the problems of the classical color image hybrid noise filtering method, a deep convolutional neural network improved by evolutionary strategy and jump connection is proposed and applied to the filtering noise reduction of color images. …”
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Convolutional neural network-based deep learning for landslide susceptibility mapping in the Bakhtegan watershed by Li Feng, Maosheng Zhang, Yimin Mao, Hao Liu, Chuanbo Yang, Ying Dong, Yaser A. Nanehkaran

“…To address this gap, this study employs a deep learning approach, utilizing a convolutional neural network (CNN) for high-precision landslide susceptibility mapping in the Bakhtegan watershed, southwestern Iran. …”
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