TFNet: point cloud Semantic Segmentation Network based on Triple feature extraction by Yong Li, Falin Chen, Qi Lin, Zhen Li, Dongxu Gao, Jingchao Yang

“…To address these challenges, we propose TFNet, an end-to-end deep neural network specifically designed to enhance local geometric feature extraction and improve performance on density variations. …”
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Dynamic Graph Neural Network for Garbage Classification Based on Multimodal Feature Fusion by Yuhang Yang, Yuanqing Luo, Yingyu Yang, Shuang Kang

“…In this paper, we introduce a novel garbage classification approach that leverages a dynamic graph neural network based on multimodal feature fusion. Specifically, the proposed method employs an enhanced Residual Network Attention Module (RNAM) network to capture deep semantic features and utilizes CIELAB color (LAB) histograms to extract color distribution characteristics, achieving a complementary integration of multimodal information. …”
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A human pose estimation network based on YOLOv8 framework with efficient multi-scale receptive field and expanded feature pyramid network by Shaobin Cai, Han Xu, Wanchen Cai, Yuchang Mo, Liansuo Wei

“…To address these issues, we propose EE-YOLOv8, a human pose estimation network based on the YOLOv8 framework, which integrates Efficient Multi-scale Receptive Field (EMRF) and Expanded Feature Pyramid Network (EFPN). …”
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A Multi-Granularity Features Representation and Dimensionality Reduction Network for Website Fingerprinting by Yaojun Ding, Bingxuan Hu

“…The network then uses a Transformer Encoder to capture more robust global features from the low-dimensional data. …”
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Enhancing Text Similarity Measurement with Hybrid Siamese Neural Networks and Lexical Features by Bei Zhou

“…Evaluation across three distinct datasets demonstrates the superiority of the hybrid Siamese neural network model, leveraging convolutional networks and lexical features, showcasing higher Pearson's correlation and lower mean square errors (MSE) compared to literature models. …”
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Re-Calibrating Network by Refining Initial Features Through Generative Gradient Regularization by Naim Reza, Ho Yub Jung

“…The experiments show that implementing this method on a pre-trained network effectively re-calibrates the network and augments higher variance filters of the initial layer of the network, which helps produce refined features. …”
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TransFINN “Transparent Feature Integrated Neural Network for Text Feature Selection and Classification” by Saif Ur Rehman, Ramsha Jat, Muhammad Rafi, Jaroslav Frnda

“…This paper introduces TransFINN, a transparent extension artificial neural network that combines transparent feature selection with text classification. …”
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Urban Land Use Classification Model Fusing Multimodal Deep Features by Yougui Ren, Zhiwei Xie, Shuaizhi Zhai

“…However, existing methods predominantly rely on either raster structure deep features through convolutional neural networks (CNNs) or topological structure deep features through graph neural networks (GNNs), making it challenging to comprehensively capture the rich semantic information in remote sensing images. …”
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Cultural transmission, networks, and clusters among Austronesian-speaking peoples by Joshua C. Macdonald, Javier Blanco-Portillo, Marcus W. Feldman, Yoav Ram

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From Convolutional Networks to Vision Transformers: Evolution of Deep Learning in Agricultural Pest and Disease Identification by Mengyao Zhang, Chaofan Liu, Zihan Li, Baoquan Yin

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Informal networks of corruption in contemporary Lithuania: Between practice and interpretation (an attempt to study evolution of blat) by Donatas Brandišauskas

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Integrating artificial intelligence with network evolution theory for community behavior prediction in dynamic complex systems by Yongyan Zhao, Jian Li

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Survey on network system security metrics by Chensi WU, Weiqiang XIE, Yixiao JI, Su YANG, Ziyi JIA, Song ZHAO, Yuqing ZHANG

“…With the improvement for comprehensive and objective understanding of the network system,the research and application of network system security metrics (NSSM) are noticed more.The quantitative evaluation of network system security is developing towards precision and objectification.NSSM can provide the objective and scientific basis for the confrontation of attack-defense and decision of emergency response.The global metrics of network system security is a crucial point in the field of security metrics.From the perspective of global metrics,the status and role of global metrics in security evaluation were pointed out.Three development stages of metrics (perceiving,cognizing and deepening) and their characteristics were analyzed and summarized.The process of global metrics was described.The metrics models,metrics systems and metrics tools were analyzed,and their functions,interrelations,and features in security metrics were pointed out.Then the technical challenges of global metrics of network systems were explained in detail,and ten opportunities and challenges were summarized in tabular form.Finally,the next direction and development trend of network system security metrics research were forecasted.The survey shows that NSSM has a good application prospect in network security.…”
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Evolution and Motivation of the Value-Added Trade Pattern of Producer Services Based on a Complex Network by Yan Li, Xuehan Liang, Sizhe Guan, Qingbo Huang

“…The DVA network has a small-world topological structure, while the FVA network does not have this feature most years. (2) Western countries, represented by the USA, Germany, and the UK, are located at the hub of the global value network, while China’s network status is rising and gradually occupying a core position not only in the Asian region but also in the world. …”
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Race estimation with deep networks by Mazida A. Ahmed, Ridip Dev Choudhury, Kishore Kashyap

“…Identifying race, which is a major physical feature in humans, is still a challenging task owing much to the lack of a concrete definition of race and the diversity of population across the globe. …”
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Optimizing Fractional-Order Convolutional Neural Networks for Groove Classification in Music Using Differential Evolution by Jiangang Chen, Pei Su, Daxin Li, Junbo Han, Gaoquan Zhou, Donghui Tang

“…This study presents a differential evolution (DE)-based optimization approach for fractional-order convolutional neural networks (FOCNNs) aimed at enhancing the accuracy of groove classification in music. …”
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Evolution of the Structure of Double-Layer Technology Cooperation-Transfer Networks and Its Impact on Innovation Capabilities by Chen Yuling, Xing Hexiang, Du Debin

“…It characterizes the basic evolutionary features of this double-layer network, analyzes the structural development differences between the collaboration and transfer subnetworks, investigates the dynamics of their coupling evolution, and explores the spatial spillover effects of the dual-layer network structure on urban innovation capacity. …”
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Evaluating Feature Impact Prior to Phylogenetic Analysis Using Machine Learning Techniques by Osama A. Salman, Gábor Hosszú

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Features of digital management of modern economy by F. F. Sharipov, M. A. Dyakonova, M. Xu

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Network-Based Hierarchical Feature Augmentation for Predicting Road Classes in OpenStreetMap by Müslüm Hacar, Diego Altafini, Valerio Cutini

“…Addressing this challenge, our research introduces a novel hierarchical feature augmentation approach to developing machine learning classifiers by the features retrieved from various levels of road network connectivity. …”
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