An Effective Fault Feature Extraction Method for Gas Turbine Generator System Diagnosis by Jian-Hua Zhong, JieJunYi Liang, Zhi-Xin Yang, Pak Kin Wong, Xian-Bo Wang

“…To improve the diagnostic performance in the GTGS, an effective fault feature extraction framework is proposed to solve the problem of the signal disorder and redundant information in the acquired signal. …”
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Visual Place Recognition Based on Dynamic Difference and Dual-Path Feature Enhancement by Guogang Wang, Yizhen Lv, Lijie Zhao, Yunpeng Liu

“…Aiming at the problem of appearance drift and susceptibility to noise interference in visual place recognition (VPR), we propose DD–DPFE: a Dynamic Difference and Dual-Path Feature Enhancement method. …”
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Insulator Surface Defect Detection Method Based on Graph Feature Diffusion Distillation by Shucai Li, Na Zhang, Gang Yang, Yannong Hou, Xingzhong Zhang

“…Aiming at the difficulties of scarcity of defect samples on the surface of power insulators, irregular morphology and insufficient pixel-level localization accuracy, this paper proposes a defect detection method based on graph feature diffusion distillation named GFDD. The feature bias problem is alleviated by constructing a dual-division teachers architecture with graph feature consistency constraints, while the cross-layer feature fusion module is utilized to dynamically aggregate multi-scale information to reduce redundancy; the diffusion distillation mechanism is designed to break through the traditional single-layer feature transfer limitation, and the global context modeling capability is enhanced by fusing deep semantics and shallow details through channel attention. …”
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Adaptive information-constrained mapping for feature compression in edge AI and federated systems by Viacheslav Kovtun

“…Abstract This article explores the problem of efficient feature compression in distributed intelligent systems with limited resources, particularly within the context of Edge AI and Federated Learning. …”
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Multiscale Feature Filtering Network for Image Recognition System in Unmanned Aerial Vehicle by Xianghua Ma, Zhenkun Yang, Shining Chen

“…To solve this problem, a multiscale feature filtering network (MFFNet) is proposed in this paper for image recognition system in the UAV. …”
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Object Tracking Algorithm Based on Multi-Layer Feature Fusion and Semantic Enhancement by Jing Wang, Yanru Wang, Dan Yuan, Yuxiang Que, Weichao Huang, Yuan Wei

“…However, this algorithm exhibits insufficient tracking accuracy and boundary box drift when dealing with similar background clutter, which directly affects the subsequent tracking process. To overcome this problem, this paper constructs a semantic enhancement model, which utilizes multi-layer feature representations extracted from deep networks, and correlates and fuses shallow features with deep features by using cross-attention. …”
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Leaf disease detection and classification in food crops with efficient feature dimensionality reduction. by Khasim Syed, Shaik Salma Asiya Begum, Anitha Rani Palakayala, G V Vidya Lakshmi, Sateesh Gorikapudi

“…This study proposes a computer vision system that integrates BiLSTM with CNN features for image categorization tasks. The system effectively reduces feature dimensionality using learned features, addressing the high dimensionality problem in leaf image data and enabling early, accurate disease identification. …”
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Joint boundary-aware and multi-feature fusion for point cloud semantic segmentation by LU Jian, ZHAO Jie, GUO Huihui, LIANG Youcheng, ZHENG Yufei

“…Current point cloud semantic segmentation methods based on deep learning tend to overlook the boundary of objects in transition area, resulting in the problem of ambiguous features at the boundary. This article proposed a point cloud semantic segmentation method with boundary-aware and multi-feature fusion (BA-MFF). …”
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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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Revisiting social responsibility as a characteristic feature of social interactions in various fields by В. Yu. Ashinov, А. R. Kumpilova

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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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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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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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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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Fine-Grained Aircraft Recognition Based on Dynamic Feature Synthesis and Contrastive Learning by Huiyao Wan, Pazlat Nurmamat, Jie Chen, Yice Cao, Shuai Wang, Yan Zhang, Zhixiang Huang

“…Second, to tackle the long-tail distribution problem, we design a dynamic feature hallucination module that synthesizes diverse hallucinated samples, thereby improving the feature diversity of tail categories. …”
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DMFFNet: Dual-Mode Multiscale Feature Fusion-Based Pedestrian Detection Method by Ruizhe Hu, Ting Rui, Yan Ouyang, Jinkang Wang, Qunyan Jiang, Yinan Du

“…To address this problem, we propose a dual-modal multi-scale feature fusion network (DMFFNet). …”
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FEATURES OF LIFE PERSPECTIVE OF FORCED DISPLACED PERSONS DURING ARMED CONFLICT IN UKRAINE by Harkusha Inesa, Dubinskyi Serhii

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Specific Features of Building Business-Processes Controlling Systems in Conditions of Economy Digitalization by E. A. Matushevskaya, O. S. Dotsenko

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Features of Distance Learning in Higher Education Institutions in The Context of The Covid-19 Pandemic by Oksana N. Goncharova, Milera Yu. Halilova

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Features of Hydrogen-Enriched Methane–Air Flames Propagating in Hele-Shaw Channels by Sergey Yakush, Sergey Rashkovskiy, Maxim Alexeev, Oleg Semenov

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