Leveraging Topic Features in Prediction of Social Network Community Evolutions by Rahman Nahi Abid, Hassan Naderi

“…Most studies in this field have focused on complex network structural features, overlooking the influence of topics and their features on network complexity and time consumption. …”
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Insights into Galaxy Evolution from Interpretable Sparse Feature Networks by John F. Wu

“…Learning the relationship between pixel-level features and galaxy properties is essential for building a physical understanding of galaxy evolution, but we are still unable to explicate the details of how deep neural networks represent image features. …”
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Community evolution prediction based on feature change patterns in social networks by Jingyi Ding, Guojing Sun, Tiwen Wang, Licheng Jiao, Junzhao Du, Jianshe Wu, Hongfei Wang, Ruohui Cheng

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Study of the Faults Network of Kunashir Island (Kuril Islands) in Order to Reconstruct the Features of its Tectonic Evolution by Krikun Nikita Sergeevich, Abdrahmanov Il'nur, Talovina Irina

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A multimodal deep learning model with differential evolution-based optimized features for classification of power quality disturbances by Md Nurul Islam

Subjects: “…Multimodal feature fusion…”
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Feature learning and generalization in deep networks with orthogonal weights by Hannah Day, Yonatan Kahn, Daniel A Roberts

“…We speculate that this structure preserves finite-width feature learning while reducing overall noise, thus improving both generalization and training speed in deep networks with depth comparable to width. …”
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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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Enhanced Peer-to-Peer Botnet Detection Using Differential Evolution for Optimized Feature Selection by Sangita Baruah, Vaskar Deka, Dulumani Das, Utpal Barman, Manob Jyoti Saikia

“…Employing differential evolution, we propose a feature selection approach that enhances the ability to discern peer-to-peer (P2P) botnet traffic amidst evolving cyber threats. …”
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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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Feature Graph Construction With Static Features for Malware Detection by Binghui Zou, Chunjie Cao, Longjuan Wang, Yinan Cheng, Chenxi Dang, Ying Liu, Jingzhang Sun

“…Malware can greatly compromise the integrity and trustworthiness of information and is in a constant state of evolution. Existing feature fusion-based detection methods generally overlook the correlation between features. …”
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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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An Effective Network Intrusion Detection System Using Recursive Feature Elimination Technique by Narendra Singh Yadav, Vijay Prakash Sharma, D. Sikha Datta Reddy, Saswati Mishra

“…These systems are proposed to identify and classify cyber-attacks on the network. However, an exhaustive assessment and performance evolution of various machine learning algorithms remains unavailable. …”
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FGBNet: A Bio-Subspecies Classification Network with Multi-Level Feature Interaction by Yang Yuan, Danping Huang, Bingbin Cai, Yang Shen, Jingdan Wang, Jiale Xv, Siyu Chen

“…Through experimentation and optimization, the ConvNeXt is selected as the backbone network for FGBNet feature extraction, and the effectiveness of the multi-level feature interaction method is verified. …”
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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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General model for best feature extraction of EEG using discrete wavelet transform wavelet family and differential evolution by Ahmad al-Qerem, Faten Kharbat, Shadi Nashwan, Staish Ashraf, khairi blaou

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Dynamic facial expression recognition integrating spatiotemporal features by LIU Baobao, TAO Lu, YANG Jingjing, WANG Heying

“…To address the challenges of extracting key facial features and capturing the dynamic changes of expressions in natural environments, a network model based on keyframes, named three-dimensional resnet and attention mechanism with GRU (TDRAG) was proposed. …”
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Temporal Graph Attention Network for Spatio-Temporal Feature Extraction in Research Topic Trend Prediction by Zhan Guo, Mingxin Lu, Jin Han

“…This necessity arises from the fact that research topics exhibit both temporal trend features and spatial correlation features. This study proposes a Temporal Graph Attention Network (T-GAT) to extract the spatio-temporal features of research topics and predict their trends. …”
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Evolution of the Limpopo River Basin in Botswana based on morphometric and morphotectonic features from selected rivers using GIS techniques by One Moses, Read B Mapeo, Joyce G Maphanyane

“…This study used morphometric techniques to generate new information describing the evolution and hydrogeological behaviour of the Limpopo River Basin in Botswana, based on the analysis of drainage surface features, form, and size. …”
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A human geography analysis of the evolution of the urban morphology of ancient Foshan city from the perspective of Cantonese trading culture by Shaobin Wang, Ye Hou, Weihui Zhang, Cheng Liao, Rongyi Wang

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Multilevel Feature Cross-Fusion-Based High-Resolution Remote Sensing Wetland Landscape Classification and Landscape Pattern Evolution Analysis by Sijia Sun, Biao Wang, Zhenghao Jiang, Ziyan Li, Sheng Xu, Chengrong Pan, Jun Qin, Yanlan Wu, Peng Zhang

“…To address these issues, this study proposes the multilevel feature cross-fusion wetland landscape classification network (MFCFNet), which combines the global modeling capability of Swin Transformer with the local detail-capturing ability of convolutional neural networks (CNNs), facilitating discerning intraclass consistency and interclass differences. …”
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