Combining Feature Extraction Methods and Categorical Boosting to Discriminate the Lettuce Storage Time Using Near-Infrared Spectroscopy by Xuan Zhou, Xiaohong Wu, Zhihang Cao, Bin Wu

“…These four feature extraction methods can solve the problem of small sample sizes. …”
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Efficient GDD feature approximation based brain tumour classification and survival analysis model using deep learning by M. Vimala, SatheeshKumar Palanisamy, Sghaier Guizani, Habib Hamam

“…The problem of brain tumor classification (BTC) has been approached with several methods and uses different features obtained from MRI brain scans. …”
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A Genetic Algorithm and PCA-Based Feature Selection to Improve the Failure Diagnosis Performance of Railway Vehicle Doors by Gil Hyun Kang, Ho Cheol Ki, Sang Hyun An, Juhee Choi, Chul Su Kim

“…A principal component analysis-based feature dimensional reduction with explained variance ratio was used to reduce the effect from multi-collinearity of features. …”
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NMS-KSD: Efficient Knowledge Distillation for Dense Object Detection via Non-Maximum Suppression and Feature Storage by Suho Son, Byung Cheol Song

“…The core of NMS-KSD is the integration of Non-Maximum Suppression (NMS) and channel max pooling to effectively select and store key features from the teacher model’s intermediate feature maps. …”
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The Je Sais Tout Magazine and the Features of Belle Epoque Mass Reading (A New Book by Daniel Couégnas) by Kirill A. Chekalov

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Bayesian Neural Networks With Robust Feature Interpretation for Enhanced Compressive Strength Prediction of Ultra‐High‐Performance Concrete by Tao Zhang, Ji Hao, Jie Zhang, Lina Du, Yunhao Zhang, Wenbin Jiao

“…A novel dataset comprising 799 UHPC mix designs, featuring 15 input parameters and one target variable, was curated from the literature. …”
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CD-CTFM: A Lightweight CNN-Transformer Network for Remote Sensing Cloud Detection Fusing Multiscale Features by Wenxuan Ge, Xubing Yang, Rui Jiang, Wei Shao, Li Zhang

“…Moreover, a lightweight feature pyramid module is designed to fuse multiscale features with contextual information. …”
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Features of the US Strategic Course towards Russia in the Conditions of Confrontation: Systemic Containment from the Perspective of Russophobic Manifestations by P. I. Pashkovsky, E. V. Kryzhko

“…The article considers the features of the US strategic course towards Russia in the context of aggravated relations. …”
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SPECIFIC FEATURES OF WORK AMONG THE WOMEN POPULATION IN THE ETHNIC ENVIRONMENT ON THE DON, KUBAN AND STAVROPOL REGION IN 1920–1930s by A. V. Averyanov

“…The article analyzes the problem of organizing work among the female population in the ethnic environment in the Don, Kuban and Stavropol regions. …”
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An MCM-Enhanced Compressive Sensing for Weak Fault Feature Extraction of Rolling Element Bearings under Variable Speeds by Ya He, Kun Feng, Minghui Hu, Jinmiao Cui

“…The compressive sensing (CS) theory provides a new slight to the big-data problem led by the Shannon sampling theorem in rolling element bearings condition monitoring, where the measurement matrix of CS tends to be designed by the random matrix (RM) to preserve the integrity of signal roughly. …”
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Research on land desertification in Ejin Banner from 1991 to 2021 based on Albedo-MSAVI feature space model by Xiaofang Jiang

“…This suggests that the feature space is suitable for research on desertification land classification in the area. …”
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Dilated Convolution and YOLOv8 Feature Extraction Network: An Improved Method for MRI-Based Brain Tumor Detection by Lincy Annet Abraham, Gopinath Palanisamy, Veerapu Goutham

“…Secondly, a dual feature pyramid network (DFPN) is built to provide more discriminative data for dynamic sparse attention mechanism to extract features from the shallow network and top-down routes to direct the following network modules to fuse features. …”
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FedeAMR-CFF: A Federated Automatic Modulation Recognition Method Based on Characteristic Feature Fine-Tuning by Meng Zhang, Jiankun Ma, Zhenxi Zhang, Feng Zhou

“…To address the critical challenges of high data privacy leakage risks, excessive communication overhead, and data silos in automatic modulation recognition tasks, this paper proposes a federated automatic modulation recognition method based on characteristic feature fine-tuning (FedeAMR-CFF). Specifically, the clients extract representative features through distance-based metric screening, and the server aggregates model parameters via the FedAvg algorithm and fine-tunes the model using the collected features. …”
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HierbaNetV1: a novel feature extraction framework for deep learning-based weed identification by Justina Michael, Thenmozhi Manivasagam

“…Originality is brought by addressing the problem of varying-sized region of interest (ROI) in an image by extracting features using diversified filters. …”
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Optimal feature selection for a weighted k-nearest neighbors for compound fault classification in wind turbine gearbox by Samuel M. Gbashi, Paul A. Adedeji, Obafemi O. Olatunji, Nkosinathi Madushele

“…However, the basic k-NN model is constrained by the curse of dimensionality, rendering it ineffective at capturing the dynamics in high-dimensional turbine gearbox vibration signals. To address this problem, this study advanced a framework for choosing the best features for a k-NN fault diagnostic model while also leveraging the benefits of “weighting” to further improve its performance. …”
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Features of using artificial intelligence technologies in the self-education activities of academic and pedagogical staff in higher education institutions by Samko Alla

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Proteomics and machine learning: Leveraging domain knowledge for feature selection in a skeletal muscle tissue meta-analysis by Alireza Shahin-Shamsabadi, John Cappuccitti

“…Typically, proteomics research focuses narrowly on using a limited number of datasets, hindering cross-study comparisons, a problem that can potentially be addressed by machine learning. …”
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A reliable NLOS error identification method based on LightGBM driven by multiple features of GNSS signals by Xiaohong Zhang, Xinyu Wang, Wanke Liu, Xianlu Tao, Yupeng Gu, Hailu Jia, Chuanming Zhang

“…In severe cases, NLOS errors can cause a ranging error of hundreds of meters, which has a substantial impact on the precision and dependability of GNSS positioning. To address this problem, we propose a reliable NLOS error identification method based on the Light Gradient Boosting Machine (LightGBM), which is driven by multiple features of GNSS signals. …”
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Features of industrial policy of the state and deve lopment of the human capita l in connection with an import substitution pro blem by A. Fedotov, D. Sockov

“…This article discusses the features of the industrial policy of the State and human capital development, in connection with the problem of import substitution goods previously imported from EU countries and North America. …”
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Psychomedical named entity recognition method based on multi-level feature extraction and multi-granularity embedding fusion by Zixuan Liu, Guofang Zhang, Yanguang Shen

“…Migrating NER models from the general purpose domain to the psychomedical domain are not effective in improving entity recognition accuracy. To solve this problem, we propose a NER method based on multi-level feature extraction and multi-granularity embedding fusion (MFME-NER), which aims to provide an innovative solution. …”
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