Crop classification with deep convolutional neural network based on crop feature by Mohamad Reza Gili, Davoud Ashourloo, Hosein Aghighi, Ali Akbar Matkan, Alireza SHakiba

“…Agricultural land cover is relatively dynamic and variable at relatively short intervals. This makes it difficult to classify crops on satellite imagery (Bargiel, 2017). …”
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Deep learning analysis of exercise stress electrocardiography for identification of significant coronary artery disease by Hsin-Yueh Liang, Hsin-Yueh Liang, Kai-Cheng Hsu, Kai-Cheng Hsu, Kai-Cheng Hsu, Shang-Yu Chien, Chen-Yu Yeh, Ting-Hsuan Sun, Meng-Hsuan Liu, Kee Koon Ng

“…The principal predictive feature variables were sex, maximum heart rate, and ST/HR index. …”
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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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CLASSIFICATION OF ARRHYTHMIA DISEASES BY THE CONVOLUTIONAL NEURAL NETWORK METHOD BASED ON ECG IMAGES by Agustian Arditya Pratama, Agus Maman Abadi

“…The input variable in the classification process with CNN is an ECG image. …”
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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

“…Once there is enough evidence to determine a 3D model, the retrieval process will be terminated ahead of time. The variable view matching method further reduces the number of similarity matching by 21.4%. …”
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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

“…While x-ray micro-computed tomography gives us three-dimensional images of the porous media, it is often impossible to quantify the variability of the pore, grains, structure, and orientation experimentally. …”
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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

“…These challenges include the lack of a balanced dataset, high variability within melanoma lesions, differences in the locations of skin lesions in images, the similarity between different skin lesions, and the presence of various artifacts. …”
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Rolling Bearing Fault Diagnosis Method Based on SWT and Improved Vision Transformer by Saihao Ren, Xiaoping Lou

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Transferring Learned ECG Representations for Deep Neural Network Classification of Atrial Fibrillation with Photoplethysmography by Jayroop Ramesh, Zahra Solatidehkordi, Raafat Aburukba, Assim Sagahyroon, Fadi Aloul

“…We derive and feed heart rate variability (HRV) and pulse rate variability (PRV) features as auxiliary inputs to the framework for robustness. …”
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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

“…Third, a CNN is trained to approximate the filtered burning rates as a function of LES scalar quantities: progress variable, local equivalence ratio, and flame thickening due to filtering. …”
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