Blind Recognition of Convolutional Codes Based on the ConvLSTM Temporal Feature Network by Lu Xu, Yixin Ma, Rui Shi, Juanjuan Li, Yijia Zhang

“…To tackle this problem, we propose ConvLSTM-TFN (temporal feature network), an innovative blind-recognition network that integrates convolutional layers, long short-term memory (LSTM) networks, and a self-attention mechanism. …”
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Histological and immunohistochemical features of the ovarian malignant epithelial tumors and granulosa cell tumors by O. A. Savchenko, I. S. Shponka, V. R. Skoryk, P. V. Savchenko

“…On the other hand, there is a problem of reliable verification of the diagnosis. …”
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Revisiting social responsibility as a characteristic feature of social interactions in various fields by В. Yu. Ashinov, А. R. Kumpilova

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Method for extracting ship shaft rate features by fusing acoustic and magnetic field by Taotao Xie, Qing Ji, Peng Yu, Jiawei Zhang

“…Finally, the shaft-rate features are extracted based on the greatest common divisor (GCD) method. …”
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A New Method for Weak Fault Feature Extraction Based on Improved MED by Junlin Li, Jingsheng Jiang, Xiaohong Fan, Huaqing Wang, Liuyang Song, Wenbin Liu, Jianfeng Yang, Liangchao Chen

“…Because of the characteristics of weak signal and strong noise, the low-speed vibration signal fault feature extraction has been a hot spot and difficult problem in the field of equipment fault diagnosis. …”
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Postradiative stenosis of the spinal canal: features of the clinic, diagnosis and treatment (clinical case) by O. V. Sklyarenko, S. N. Larionov, A. P. Zhivotenko, V. A. Sorokovikov, A. V. Gorbunov, V. E. Potapov

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Fine-grained flood disaster information extraction incorporating multiple semantic features by Shunli Wang, Rui Li, Huayi Wu, Jiang Li, Yun Shen

“…As a crucial source for disaster monitoring, social media data exhibits high variability and ambiguity, with current research lacking targeted multidimensional semantic analysis, resulting in coarse granularity and limited accuracy. To address this problem, this study proposes a framework and method synthesizing multiple semantic features to extract fine-grained disaster information. …”
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Orbital Solitary Fibrous Tumor: Four Case Reports—Clinical and Histopathological Features by Carmen Navarro-Perea, Cristina Calleja-García, Álvaro Bengoa-González, María-C. Garrido, Enrique Mencía-Gutiérrez, Silvia Pérez-Trigo

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Transferable Feature Representation for Visible-to-Infrared Cross-Dataset Human Action Recognition by Yang Liu, Zhaoyang Lu, Jing Li, Chao Yao, Yanzi Deng

“…Motivated by the idea of transfer learning, an infrared human action recognition framework using auxiliary data from visible light is proposed to solve the problem of limited infrared action data. In the proposed framework, we first construct a novel Cross-Dataset Feature Alignment and Generalization (CDFAG) framework to map the infrared data and visible light data into a common feature space, where Kernel Manifold Alignment (KEMA) and a dual aligned-to-generalized encoders (AGE) model are employed to represent the feature. …”
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Features of direct measurements for evaluation of the volume activity of radionuclides in the air of the working area by A. S. Gerasimenko, S. V. Dorokhov, V. V. Krivorotova

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Features of some transcription factors gene expression in the malignancy tissues of the corpus uteri by D. S. Kutilin, I. S. Nikitin, O. I. Kit

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Features of the vegetative state and arterial pressure level in children with chronic gastroduodenal pathology by T. M. Mikhieieva, D. Yu. Nechytailo, V. V. Poniuk, T. P. Fomina

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A Multi-Granularity Features Representation and Dimensionality Reduction Network for Website Fingerprinting by Yaojun Ding, Bingxuan Hu

“…This degradation results from the evolution of network protocol versions and the ongoing development of obfuscation techniques, a phenomenon known as concept drift. To address the problem of concept drift, this paper presents a multi-granularity features representation and dimensionality reduction network for Website Fingerprinting, referred to as LRCT. …”
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CLINICAL AND ULTRASONIC FEATURES OF MULTIPLE OSTEOMYELITIS IN PURULENT-SEPTIC DISEASE FORM IN CHILDREN by S. A. Polkovnikova, V. D. Zavadovskaya, A. P. Kurazhov, V. M. Maslikov, V. V. Shalygin

“…Aim of a research diagnostic aspects of acute haematogenic osteomyelitis (AGO) represent a significant problem due more frequent occurrence of multiple osteomyelitis.Objective. …”
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Features and benefi ts of using new forms of antibiotics with improved pharmacokinetic properties by А. L. Vertkin, M. M. Shamuilova, G. Yu. Knorring

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Features of the perception and interpretation of Girolamo Savonarola’s ideas by his contemporaries. The Benivieni dialogue by E. P. Telmenko

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A New Proposed Hybrid Learning Approach with Features for Extraction of Image Classification by Mohanad Azeez Joodi, Muna Hadi Saleh, Dheyaa Jasim Kadhim

“…Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. …”
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Corrupted Point Cloud Classification Through Deep Learning with Local Feature Descriptor by Xian Wu, Xueyi Guo, Hang Peng, Bin Su, Sabbir Ahamod, Fenglin Han

“…In this article, we use local feature descriptors as a preprocessing method to extract features from point cloud data and propose a new neural network architecture aligned with these local features, effectively enhancing performance even in extreme cases of data corruption. …”
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AFMF: adaptive fusion of multi-hop neighborhood features in graph convolutional network by Kang Liu, Xinyu Li, Lian Liu, Zhihao Xv, Aohang Pei, Runshi Ji

“…To address this issue, we propose a graph convolutional network based on Adaptive Fusion of Multi-hop Features, termed AFMF, which can adaptively generate feature fusion weights according to the features of multi-hop nodes, solving the over-smoothing problem caused by shared fusion weights. …”
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PFVnet, a feature enhancement network for low recognition coal and rock images by Cai Han, Zhenwen Liu, Shenglei Zhao, Yubo Li, Yanwei Duan, Xinzhou Yang, Chuanbo Hao

“…We characterized the grayscale and texture feature patterns of coal-rock media under varying degrees of interference and established a comprehensive multi-element image training sample library. …”
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