Feature Interaction and Adaptive Fusion Network With Spectral Modulation for Pansharpening by Lihua Jian, Jiabo Liu, Lihui Chen, Di Zhang, Gemine Vivone, Xichuan Zhou

“…This article introduces a feature interaction and adaptive fusion network (FIAFN) with spectral modulation for pansharpening to address these issues. …”
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Spoofed Speech Detection with Weighted Phase Features and Convolutional Networks by Gökay Dişken

“…The extracted features are then fed to a convolutional neural network as input. …”
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Grape Leaf Diseases Identification System Using Convolutional Neural Networks and LoRa Technology by Zinon Zinonos, Socratis Gkelios, Ala F. Khalifeh, Diofantos G. Hadjimitsis, Yiannis S. Boutalis, Savvas A. Chatzichristofis

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Hybrid feature learning framework for the classification of encrypted network traffic by S. Ramraj, G. Usha

“…The focus of this research is to evaluate the performance of the Support Vector Machine (SVM) in classifying network packets by application type, as well as classifying the type of data communicated within an application. …”
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Formation Features of the Customer Segments for the Network Organizations in the Smart Era by Elena V. Yaroshenko

“…This purpose has defined the statement and the solution of the following tasks: to explore characteristic features of the network forms of the organization of economic activity of the companies, their prospects, Smart technologies’ influence on them; to reveal the work importance with different client profiles; to explore the existing methods and tools of formation of key customer segments; to define criteria for selection of key groups; to reveal the characteristics of customer segments’ formation for the network organizations.In the research process, methods of the system analysis, a method of analogies, methods of generalizations, a method of the expert evaluations, methods of classification and clustering were applied.This paper explores the characteristics and principles of functioning of network organizations, the appearance of which is directly linked with the development of Smart society. …”
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SLFCNet: an ultra-lightweight and efficient strawberry feature classification network by Wenchao Xu, Yangxu Wang, Jiahao Yang

“…Methods In this study, we have developed a lightweight model capable of real-time detection and classification of strawberry fruit, named the Strawberry Lightweight Feature Classify Network (SLFCNet). This innovative system incorporates a lightweight encoder and a self-designed feature extraction module called the Combined Convolutional Concatenation and Sequential Convolutional (C3SC). …”
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The influence of correlated features on neural network attribution methods in geoscience by Evan Krell, Antonios Mamalakis, Scott A. King, Philippe Tissot, Imme Ebert-Uphoff

“…Correlated features may also cause inaccurate attributions because XAI methods typically evaluate isolated features, whereas networks learn multifeature patterns. …”
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Software Defect Prediction through Neural Network and Feature Selections by Mutasem Shabeb Alkhasawneh

“…To predict the software defect, this study proposed a model consisting of feature selection and classifications. The correlation base method was used for feature selection, and radial base function neural network (RBF) was used for classification. …”
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Structural Evaluation for Distribution Networks with Distributed Generation Based on Complex Network by Fei Xue, Yingyu Xu, Huaiying Zhu, Shaofeng Lu, Tao Huang, Jinling Zhang

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Predicting the Evolution of the Supercontinuum Generation With CNN-LSTM Model by Yi Feng, Ruiyuan Liu, Xinyue Chang, Xiangzhen Huang, Yuan He, Ning Li, Tiantian Zhou, Chujun Zhao

“…We propose a hybrid deep learning model, namely convolutional neural network–long short-term memory (CNN-LSTM) approach to investigate the evolution of the supercontinuum (SC) generation numerically. …”
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Evaluating the Performance of Machine Learning Classifiers for Network Intrusion Detection: A Comparative Study Using the UNSW-NB15 Dataset by Iwan Handoyo Putro

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Network growth under opportunistic attachment by Carolina E. S. Mattsson

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Myocarditis Diagnosis Using Semi-Supervised Generative Adversarial Network and Differential Evolution by Haifeng Gui, Na Zhang

“…A diagnostic model for myocarditis is introduced in this paper, utilizing CMR images and employing a semi-supervised generative adversarial network (SS-GAN) to enhance classifier performance, complemented by differential evolution (DE) for hyperparameter optimization. …”
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Comprehensive Style Transfer for Facial Images Using Enhanced Feature Attribution in Generative Adversarial Nets by Yongseon Yoo, Seonggyu Kim, Jong-Min Lee

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Research on Sentiment Tendency and Evolution of Public Opinions in Social Networks of Smart City by Yanni Liu, Dongsheng Liu, Yuwei Chen

“…In order to get more valuable information and implement effective supervision on public opinions, it is necessary to study the public opinions, sentiment tendency, and the evolution of the hot events in social networks of a smart city. …”
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Aggregated Time Series Features in a Voxel-Based Network Architecture by Zsolt Vincze, Andras Rovid

“…During the evaluation, the authors examine the object detection performance of a popular voxel-based neural network with its original architecture and several variants where the time domain related features were propagated through the network and aggregated at different stages of processing. …”
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Network of Settlements in Novosibirsk District in 1920s: Population, Structure and Development Features by A. I. Tatarnikova

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Image denoising based on deep feature fusion and U-Net network by Yong Zhang

“…Therefore, we propose a novel image denoising method based on deep feature fusion and U-Net network. This new method uses a two-branch U-Net network to fuse features and preserve image texture. …”
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Graph Attention Neural Network Model With Behavior Features for Knowledge Tracking by Wei Zhang, Sen Hu, Kaiyuan Qu

“…In order to solve the above problems, a graph attention neural network model with behavior features for knowledge tracking (GAKT-BF) is proposed in this paper. …”
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Hybrid Random Feature Selection and Recurrent Neural Network for Diabetes Prediction by Oyebayo Ridwan Olaniran, Aliu Omotayo Sikiru, Jeza Allohibi, Abdulmajeed Atiah Alharbi, Nada MohammedSaeed Alharbi

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