Application of Permutation Entropy in Feature Extraction for Near-Infrared Spectroscopy Noninvasive Blood Glucose Detection by Xiaoli Li, Chengwei Li

“…Finally, the support vector regression and partial least square regression are used to establish the mathematical model between the characteristic spectral data and glucose concentration, and the results are compared with conventional feature extraction methods. Results show that the proposed new method can extract useful information from near-infrared spectra, effectively solve the problem of characteristic wave band extraction, and improve the analytical accuracy of spectral and model stability.…”
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Preliminary Validation of Multimodal Feature Matching Method for Multi-source DEM Registration in Planetary Scenarios by Y. Zhang, G. Wan, D. Liu, T. Tao, C. Xiao, C. Xiao, Z. Ye, Z. Ye, X. Tong, X. Tong

“…The results of image feature matching experiments demonstrate that the Weighted Structure Saliency Feature (WSSF) method outperforms other existing state-of-the-art multimodal matching methods. …”
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Research on fault feature enhancement and diagnosis of marine water pump bearing based on BM-MTF by Zhiqiang LIAO, Zhende HUANG, Xuewei SONG, Guanlong LIANG, Baozhu JIA

“…ObjectiveMarine water pump bearings operate in complex environments, and the fault features in the acquired signals are easily submerged by noise, resulting in low fault diagnosis accuracy. …”
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An Intrusion Detection Model Based on Feature Selection and Improved One-Dimensional Convolutional Neural Network by Qingfeng Li, Bo Li, Linzhi Wen

“…The problem of intrusion detection has new solutions, thanks to the widespread use of machine learning in the field of network security, but it still has a few issues at this time. …”
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Research on the performance of the SegFormer model with fusion of edge feature extraction for metal corrosion detection by Bingnan Yan, Conghui Wang, Xiaolong Hao

“…In this paper, a SegFormer metal corrosion detection method based on parallel extraction of edge features is proposed. Firstly, to solve the boundary ambiguity problem of metal corrosion images, an edge-feature extraction module (EEM) is introduced to construct a spatial branch of the network to assist the model in extracting shallow details and edge information from the images. …”
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Research on Feature Extraction Method and Process Optimization of Rolling Bearing Faults Based on Electrostatic Monitoring by Ruochen Liu, Han Yin, Jianzhong Sun, Lanchun Zhang

“…In order to solve this problem, a sparse representation based on cluster-contraction stagewise orthogonal matching pursuit (CcStOMP) is proposed to extract the fault features in the electrostatic signals of rolling bearings. …”
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Enhanced forecasting of emergency department patient arrivals using feature engineering approach and machine learning by Bruno Matos Porto, Flavio Sanson Fogliatto

“…Abstract Background Emergency department (ED) overcrowding is an important problem in many countries. Accurate predictions of ED patient arrivals can help management to better allocate staff and medical resources. …”
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PCL-RC: a parallel cloud resource load prediction model based on feature optimization by Guoxiu Zhang, Xinyi He, Xiaofeng Wang

“…To address the problem of nonlinear load data feature extraction, a feature extraction optimization method that is based on combining an improved random forest method and complete ensemble empirical modal decomposition with adaptive noise is proposed to realize regular decomposition and feature extraction from fluctuating data. …”
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A two-branch multiscale spectral-spatial feature extraction network for hyperspectral image classification by Aamir Ali, Caihong Mu, Zeyu Zhang, Jian Zhu, Yi Liu

“…Then we densely connect series of MSEFE or MSAFE modules respectively in a two-branch framework to balance efficiency and effectiveness, alleviate the vanishing-gradient problem and strengthen the feature propagation. To evaluate the effectiveness of the proposed method, the experimental results were carried out on bench mark HSI datasets, demonstrating that TBMSSN obtained higher classification accuracy compared with several state-of-the-art methods.…”
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Improved Low-Light Image Feature Matching Algorithm Based on the SuperGlue Net Model by Fengchao Li, Yu Chen, Qunshan Shi, Ge Shi, Hongding Yang, Jiaming Na

“…The SuperGlue algorithm, which integrates deep learning theory with the SuperPoint feature extraction operator and addresses the matching problem using the classical Sinkhorn method, has significantly enhanced matching efficiency and become a prominent research focus. …”
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Parametric and nonparametric two-sample tests for feature screening in class comparison: a simulation study by Elena Landoni, Federico Ambrogi, Luigi Mariani, Rosalba Miceli

“…The tests for the general two-sample problem introduce a more general concept of 'differential expression', thus overcoming the limitations of the other tests restricted to specific moments of the feature distributions. …”
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Research and performance analysis of random forest-based feature selection algorithm in sports effectiveness evaluation by Yujiao Li, Yingjie Mu

“…In order to solve the problem of low accuracy in traditional mining methods, the study combines the random forest algorithm with the artificial raindrop algorithm, and adopts a sports data mining method based on feature selection to achieve effective analysis of sports big data. …”
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Edge-Guided Feature Pyramid Networks: An Edge-Guided Model for Enhanced Small Target Detection by Zimeng Liang, Hua Shen

“…The goal is to resolve the problem of missing target information that occurs when Feature Pyramid Networks (FPNs) perform continuous down-sampling to obtain deeper semantic features. …”
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Development of Robot Feature for Stunting Analysis Using Long-Short Term Memory (LSTM) Algorithm by Muhammad Rahadian Abdurrahman, Halim Al Aziz, Farras Adhani Zayn, Muhammad Agus Purnomo, Heru Agus Santoso

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Enhanced Intrusion Detection in In-Vehicle Networks Using Advanced Feature Fusion and Stacking-Enriched Learning by Ali Altalbe

“…This study proposes an accurate and low-complexity IDS for in-vehicle networks based on feature fusion and ensemble learning called the Feature Fusion and Stacking-based IDS (FFS-IDS). …”
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Joint feature representation optimization and anti-occlusion for robust multi-vessel tracking in inland waterways by Shenjie Zou, Jin Liu, Xiliang Zhang, Zhongdai Wu, Jing Liu, Bing Han

“…Finally, a bidirectional feature pyramid network (BiFPN) is utilized to fuse vessel appearance features from different scales, enhancing the capability to learn cross-scale features of vessels to some extent. …”
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Improving distributed systems failure prediction via multi-objective feature selection and deep forest by Zhidan Yuan, Yikai Zhang, Yingqi Yu, Taizhi Lv, Tao Huang

“…Although existing studies have used feature selection methods to address this issue, the optimal number of KPI metrics remains difficult to determine. …”
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Towards Efficient SAR Ship Detection: Multi-Level Feature Fusion and Lightweight Network Design by Wei Xu, Zengyuan Guo, Pingping Huang, Weixian Tan, Zhiqi Gao

“…To further enhance the detection capability, Efficient Feature Learning (EFL) modules are embedded in the neck to improve feature representation. …”
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A Self-Supervised Monocular Depth Estimation Framework Based on Detail Recovery and Feature Fusion by Shun Li, Chongzheng Huang, Xiangzhe Li, Zhengyou Liang

“…MDAFM captures feature information from different perspectives and levels to address the problem of critical information loss, while HPCB effectively captures and fuses local and global information through parallel processing. …”
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An improved dung beetle optimizer based on Padé approximation strategy for global optimization and feature selection by Tianbao Liu, Lingling Yang, Yue Li, Xiwen Qin

“…In this paper, we proposed a multi-strategy enhanced dung beetle optimization algorithm (mDBO) that integrates multiple strategies to effectively address the feature selection problem. First, a novel population initialization strategy based on a hybrid tent-sine map and random opposition-based learning was proposed to generate initial population. …”
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