Social and Professional Awareness by Students of Engineers Specialties of the Upcoming Digitalization (Pilot Study Experience and First Results) by P. P. Deryugin, O. S. Bannova, E. A. Kamyshina, R. E. Popov, A. N. Sidorova

“…What are the advantages and problems with the emergence of digitalization in the social space of society in the eyes of young people focused on technical education? …”
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Features of Forecasting Reliability of 6—10 kV Overhead Lines According to Statistics of their Failures and Reconditionings by Basmanov V.G.

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Selection of the Binding Object on the Current Image Formed by the Technical Vision System Using Structural and Geometric Features by Sotnikov O., Sivak V., Pavlov Ya., Нashenko S., Borysenko T., Torianyk D.

“…The solution to the first problem is based on the formation of histograms of fractal dimension depending on the number of objects in the image and identifying the features by which the object is selected. …”
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Hydrodynamic Features of Gas-Liquid Flow Movement in a Separation Device Plane Channel with an Oscillating Wall by Pavlenko I.V., Liaposhchenko O.O., Sklabinskyi V.I., Ivanov V.O., Gusak O.G.

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Improved SURF−FLANN feature extraction and matching algorithm for video stitching of fully-mechanized working face by Qinghua MAO, Menghan WANG, Xin HU, Jiao ZHAI

“…The SURF (Speed Up Robust Features) feature extraction algorithm and FLANN (Fast Library or Approximate Nearest Neighbors) feature matching algorithm in current video stitching technology have the problems of feature point extraction errors and low feature point matching accuracy in harsh environments of fully-mechanized working face. …”
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A new feature for handwritten signature image description based on local binary patterns by V. V. Starovoitov, U. Yu. Akhundjanov

“…Objectives. The problem of describing the invariant features of a digital image of handwritten signature that describes the distribution of its local features is considered. …”
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Adaptive mechanism-based grey wolf optimizer for feature selection in high-dimensional classification. by Genliang Li, Yaxin Cui, Jingyu Su

“…Feature Selection (FS) is a crucial component of machine learning and data mining. …”
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A Parallel Image Denoising Network Based on Nonparametric Attention and Multiscale Feature Fusion by Jing Mao, Lianming Sun, Jie Chen, Shunyuan Yu

“…Convolutional neural networks have achieved excellent results in image denoising; however, there are still some problems: (1) The majority of single-branch models cannot fully exploit the image features and often suffer from the loss of information. (2) Most of the deep CNNs have inadequate edge feature extraction and saturated performance problems. …”
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Non-cooperative signal modulation recognition algorithm based on joint feature parameter extraction by Haifei SI, Xingliu HU, Zhen SHI, Shiyong LI

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SVM-RFE Based Feature Selection and Taguchi Parameters Optimization for Multiclass SVM Classifier by Mei-Ling Huang, Yung-Hsiang Hung, W. M. Lee, R. K. Li, Bo-Ru Jiang

“…However, SVM only functions well on two-group classification problems. This study combines feature selection and SVM recursive feature elimination (SVM-RFE) to investigate the classification accuracy of multiclass problems for Dermatology and Zoo databases. …”
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Target detection of helicopter electric power inspection based on the feature embedding convolution model. by Dakun Liu, Wei Zhou, Linzhen Zhou, Wen Guan

“…This study aims to improve the helicopter electric power inspection process by using the feature embedding convolution (FEC) model to solve the problems of small scope and poor real-time inspection. …”
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Improved ICP point cloud registration method based on feature point extraction and PCA by Ma Ran

“…The traditional Iterative Closest Point (ICP) method for point cloud registration has problems such as poor real-time performance, susceptibility to local extremum, and low registration accuracy. …”
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Network intrusion detection method based on VAE-CWGAN and fusion of statistical importance of feature by Taotao LIU, Yu FU, Kun WANG, Xueyuan DUAN

“…Considering the problems of traditional intrusion detection methods limited by the class imbalance of datasets and the poor representation of selected features, a detection method based on VAE-CWGAN and fusion of statistical importance of features was proposed.Firstly, data preprocessing was conducted to enhance data quality.Secondly, a VAE-CWGAN model was constructed to generate new samples, addressing the problem of imbalanced datasets, ensuring that the classification model no longer biased towards the majority class.Next, standard deviation, difference of median and mean were used to rank the features and fusion their statistical importance for feature selection, aiming to obtain more representative features, which made the model can better learn data information.Finally, the mixed data set after feature selection was classified through a one-dimensional convolutional neural network.Experimental results show that the proposed method demonstrates good performance advantages on three datasets, namely NSL-KDD, UNSW-NB15, and CIC-IDS-2017.The accuracy rates are 98.95%, 96.24%, and 99.92%, respectively, effectively improving the performance of intrusion detection.…”
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Facial Expression Recognition with Multi-perspective Feature Fusion Under Deep Residual Convolution by GUAN Xiaorui, GAO Lu, SONG Wenbo, LIN Kezheng

“… Aiming at the problems of inaccurate facial expression recognition and large amount of calculation under multi-perspective in real life, a facial expression recognition model MVResNet-FER is proposed, which is based on multi-perspective feature fusion under deep residual convolution.The residual block in ResNet is first improved and the conventional convolutional network is replaced with a depthwise separable network.Second, a CBAM module is added to enhance the extraction of effective features under multi-perspective and the supplementation of shallow feature information. …”
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Rethinking feature representation and attention mechanisms in intelligent recognition of leaf pests and diseases in wheat by Yuhan Zhang, Dongsheng Liu

“…To address the above problems and needs, we rethink the feature representation and attention mechanism in intelligent recognition of wheat leaf diseases and pests, and propose a representation and recognition network (RReNet) based on the feature attention mechanism. …”
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Interpretable analysis of transformer winding vibration characteristics: SHAP and multi-classification feature optimization by Yongteng Sun, Hongzhong Ma

“…However, since SHAP tends to overlook the recall of certain states in multi-classification problems, a feature subset optimization scheme is proposed. …”
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Development of a multi-level feature fusion model for basketball player trajectory tracking by Tao Wang

“…To solve the problems of low matching degree, long tracking time, and low accuracy of multi-target tracking in the process of athlete motion trajectory tracking using deep learning technology, a new athlete motion trajectory tracking model was proposed in this study. …”
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Brain tumor intelligent diagnosis based on Auto-Encoder and U-Net feature extraction. by Yaru Cao, Fengning Liang, Teng Zhao, Jinting Han, Yingchao Wang, Haowen Wu, Kexing Zhang, Huiwen Qiu, Yizhe Ding, Hong Zhu

“…The encoder of the feature extractor based on dense block, is used to enhance feature propagation and reduce the number of parameters. …”
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An adaptive initialization and multitasking based evolutionary algorithm for bi-objective feature selection in classification by Hang Xu, Bing Xue, Mengjie Zhang

“…Abstract Evolutionary algorithms have become a widely-used approach for solving multi-objective optimization problems over the last decades, while feature selection in classification is also a discrete bi-objective optimization problem that aims at simultaneously minimizing the classification error and the number of selected features. …”
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Hybrid feature selection and classification technique for early prediction and severity of diabetes type 2. by Praveen Talari, Bharathiraja N, Gaganpreet Kaur, Hani Alshahrani, Mana Saleh Al Reshan, Adel Sulaiman, Asadullah Shaikh

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