Azimuth-Guided Feature Embedding Network With Dual Inference Mechanism for Few-Shot SAR Target Recognition by Yan Peng, Xuelian Yu, Haohao Ren, Lei Miao, Lin Zou, Yun Zhou

“…To be specific, the feature extraction model, i.e., AGFEN is composed of the azimuth embedding module (AEM) and the dynamic feature embedding network (DFEN). …”
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A Novel Improvement of Feature Selection for Dynamic Hand Gesture Identification Based on Double Machine Learning by Keyue Yan, Chi-Fai Lam, Simon Fong, João Alexandre Lobo Marques, Richard Charles Millham, Sabah Mohammed

“…The core goal is to select independent variables from a gesture identification problem that are causally related to final gesture results. …”
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DynaOOD-Net: Dynamic Progressive Feature Fusion and Energy Balancing for Robust Out-of-Distribution Detection by Jiting Zhou, Zhihao Zhou, Pu Zhang

“…DP-FPN incorporates a Multi-Branch Dynamic Fusion Block (MBDF) to enable dynamic feature interactions and progressive optimization, ensuring robust feature representation across complex scenarios. …”
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SAVL: Scene-Adaptive UAV Visual Localization Using Sparse Feature Extraction and Incremental Descriptor Mapping by Ganchao Liu, Zhengxi Li, Qiang Gao, Yuan Yuan

“…Firstly, to tackle the challenge of inaccurate localization resulting from sparse terrain features, this work proposes a novel feature extraction network grounded in a general visual model, leveraging the robust zero-shot generalization capability of the pre-trained model and extracting sparse features from UAV and satellite imagery. …”
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Evaluation of epidemiological and microbiological characteristics, clinical features, and outcomes of adult patients with infective endocarditis in Mashhad, Iran by Ali Shahini, Matin Shirazinia, Raha Jafari, Ali Akbar Heydari

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A Study on Interpretable Electric Load Forecasting Model with Spatiotemporal Feature Fusion Based on Attention Mechanism by Shuaishuai Li, Weizhen Chen

“…Traditional methods have difficulty dealing with high-dimensional nonlinear data, and the single deep learning model has the limitations of spatiotemporal feature decoupling and being a “black box”. Aiming at the problem of insufficient accuracy and interpretability of power load forecasting in a renewable energy grid connected scenario, this study proposes an interpretable spatiotemporal feature fusion model based on an attention mechanism. …”
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Multiscale Attention Feature Fusion Based on Improved Transformer for Hyperspectral Image and LiDAR Data Classification by Aili Wang, Guilong Lei, Shiyu Dai, Haibin Wu, Yuji Iwahori

“…With the uninterrupted evolution of remote sensing data, the list of available data sources has expanded, effectively utilizing useful information from multiple sources for better land surface observation, which has become an intriguing and challenging problem. However, the complexity of urban areas and their surrounding structures makes it extremely difficult to capture correlations between features. …”
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PneuX-Net: An Enhanced Feature Extraction and Transformation Approach for Pneumonia Detection in X-Ray Images by Kashif Munir, Muhammad Usama Tanveer, Hasan J. Alyamani, Amine Bermak, Atiq Ur Rehman

“…Early and precise detection is crucial to optimizing treatment strategies and reducing morbidity and mortality rates. To address this problem, we propose PneuX-Net, an ensemble-based feature extraction framework that integrates multiple machine learning (ML) models Random Forest (RF), Gaussian Naïve Bayes (GNB) and K-Nearest Centroid (KNC). …”
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Multi-Level Feature Dynamic Fusion Neural Radiance Fields for Audio-Driven Talking Head Generation by Wenchao Song, Qiong Liu, Yanchao Liu, Pengzhou Zhang, Juan Cao

“…However, previous approaches failed to distinguish the importance of different regions, resulting in the loss of information-rich region features. To alleviate the problem and improve video quality, we propose MLDF-NeRF, an end-to-end method for talking head generation, which can achieve better vector representation through multi-level feature dynamic fusion. …”
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Spatial–Spectral Feature Fusion and Spectral Reconstruction of Multispectral LiDAR Point Clouds by Attention Mechanism by Guoqing Zhou, Haoxin Qi, Shuo Shi, Sifu Bi, Xingtao Tang, Wei Gong

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Cognitive impairment and cognitive reserve, their correlations with behavioral features of patients with human immunodeficiency virus during hospitalization by O. V. Koltsova, G. Sh. Moshkova

“…The goal is to study the features of the cognitive reserve (CR) in HIV-infected patients admitted to the hospital, the relationship of CR with cognitive disorders, stress and coping strategies, taking into account the drug history.Materials and methods. …”
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Patient preferences for key organizational features of primary cardiovascular care in Quebec: a discrete choice experiment by Claudio Del Grande, Janusz Kaczorowski, Marie-Pascale Pomey

“…This study aimed to investigate the effect of key organizational features identified by patients and providers on patients’ choice of a preferred primary care practice to receive cardiovascular care. …”
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On the local features of the Sargatka Culture settlements in the Tobol River basin (based on pottery complex of the Rafailovo settlement) by Prokonova M.M., Matveeva N.P.

“…The article is concerned with the problem of determination of local variants of the Early Iron Age Sargatka Culture in Western Siberian forest-steppe. …”
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A Novel Dual-Branch Global and Local Feature Extraction Network for SAR and Optical Image Registration by Xuanran Zhao, Yan Wu, Xin Hu, Zhikang Li, Ming Li

“…However, the inherent differences between the two modalities pose a challenge to the existing deep-learning algorithms that only depend on local features. To address this problem, we propose a global and local feature extraction network (GLFE-Net) for SAR and optical image registration. …”
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DMSF-YOLO: Cow Behavior Recognition Algorithm Based on Dynamic Mechanism and Multi-Scale Feature Fusion by Changfeng Wu, Jiandong Fang, Xiuling Wang, Yudong Zhao

“…For the problem in multi-scale behavior changes of dairy cows, a multi-scale convolution module (MSFConv) is designed, and some C3k2 modules of the backbone network and neck network are replaced with MSFConv, which can extract cow behavior information of different scales and perform multi-scale feature fusion. …”
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Assessment of intraoperative fluid misdirection syndrome risk factors according to anatomical and topographical features of anterior segment by I.S. Rebrikov, E.V. Egorova, A.S. Rebrikova, A.V. Lizunov, E.M. Titarenko

“…Despite continuous improvement in cataract surgery technology, intraoperative fluid misdirection syndrome remains an underestimated problem. Purpose. To evaluate intraoperative fluid misdirection syndrome clinical manifestation in patients with pseudoexfoliation syndrome (PXS) and without it; to assess intraoperative fluid misdirection syndrome risk factors according to anatomical and topographical features of anterior segment. …”
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FEATURES OF THE USE OF MOBILE COMMUNICATION IN THE STUDENT ENVIRONMENT / ОСОБЕННОСТИ ИСПОЛЬЗОВАНИЯ МОБИЛЬНОЙ СВЯЗИ В СТУДЕНЧЕСКОЙ СРЕДЕ... by SHARIKOV ALEXANDER V . / ШАРИКОВ А.В., EROFEEV SERGEI V. / ЕРОФЕЕВ С.В.

“…The article discusses the features of mobile communication in the student environment in the context of socio-cultural transformations generated by technological progress. …”
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<i>C. difficile</i>-infection and microbyota in newborns: resolved and outstanding issues by L. N. Mazankova, S. G. Perlovskaya, O. V. Rubalchenko

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PEMFC RUL Prediction for Non-Stationary Time Series Based on Crossformer Model by Ning Zhou, He Zeng, Zefei Zheng, Ke Wang, Jianxin Zhou

“…However, the remaining useful life (RUL) issue of PEMFCs has been one of the main challenges limiting their commercialization. The RUL prediction problem of PEMFCs exhibits characteristics of time series forecasting, but its data possess multidimensional features and non-stationarity, which limits the applicability of classical time series forecasting models like the Transformer in solving the RUL prediction problem. …”
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¿Qué hacer con textos que no se pueden publicar? Datos derivados, criterios FAIR y TEI by José Calvo Tello, Nanette Rißler-Pipka

“…In the last decades different projects have published derived data (also called extracted features) to avoid this problem. In this article, we argue in favor of TEI as a format for this task, as it favors compliance with the FAIR principles. …”
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