An Effective Network Intrusion Detection System Using Recursive Feature Elimination Technique by Narendra Singh Yadav, Vijay Prakash Sharma, D. Sikha Datta Reddy, Saswati Mishra

“…This is achieved through the use of Recursive Feature Elimination (RFE). In RFE, the algorithm is run recursively until a selected number of features are identified to enhance efficiency and reduce computational cost. …”
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Features extraction based on Naive Bayes algorithm and TF-IDF for news classification. by Li Zhang

“…This work bridges the gap between traditional feature engineering and transformer-based models, offering a cost-effective solution for news platforms. …”
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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

“…Our method effectively distinguishes diverse coding features, surpassing existing models and establishing a new benchmark for channel-coding recognition.…”
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A Multi-Granularity Features Representation and Dimensionality Reduction Network for Website Fingerprinting by Yaojun Ding, Bingxuan Hu

“…The network then uses a Transformer Encoder to capture more robust global features from the low-dimensional data. Experimental results comparing LRCT with state-of-the-art WF methods demonstrate that the proposed LRCT achieves 99.34% accuracy in a closed-world scenario, outperforming other benchmark models. …”
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Underutilized Feature Extraction Methods for Burn Severity Mapping: A Comprehensive Evaluation by Linh Nguyen Van, Giha Lee

“…Machine learning (ML) models utilizing satellite-derived vegetation indices are crucial for assessing wildfire damage; however, incorporating many indices can lead to multicollinearity, reducing classification accuracy. …”
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Nonlocal and Local Feature-Coupled Self-Supervised Network for Hyperspectral Anomaly Detection by Degang Wang, Longfei Ren, Xu Sun, Lianru Gao, Jocelyn Chanussot

“…Furthermore, an improved center block masked convolution strengthens NL2Net ’s focus on surrounding background features, enhancing the background modeling effect. …”
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Spatial correlation guided cross scale feature fusion for age and gender estimation by Shiyi Jiang, Qing Ji, Hukui Shi, Che Chen, Yang Xu

“…The SCCA module introduces a novel bipartite grouping mechanism that leverages hotspot detection to preserve discriminative body features when facial cues are unavailable. Comprehensive experiments demonstrate that SCGNet achieves state-of-the-art performance with minimum Mean Absolute Error (MAE) 4.01% for age estimation on IMDB-Clean (2.9% improvement over VOLO-D1) and highest gender classification accuracy on IMDB-Clean, UTKFace, and Lagenda datasets, showing improvements in cross-scene adaptability compared to VOLO and MiVOLO models respectively. …”
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Association of radiomic features with genomic signatures in thyroid cancer: a systematic review by Neila Luciano, Francesca Maria Orlandella, Mariantonia Braile, Carlo Cavaliere, Marco Aiello, Monica Franzese, Giuliana Salvatore

“…The effectiveness of models based on US-radiomic features in predicting BRAFV600E mutation in patients with TC requires further investigation. …”
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Advanced Classifiers and Feature Reduction for Accurate Insomnia Detection Using Multimodal Dataset by Ameya Chatur, Mostafa Haghi, Nagarajan Ganapathy, Nima TaheriNejad, Ralf Seepold, Natividad Martinez Madrid

“…Our findings emphasize the importance of tailoring feature sets and employing appropriate reduction techniques for optimal predictive modeling in sleep-related studies. …”
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Automatic feature selection and weighting in molecular systems using Differentiable Information Imbalance by Romina Wild, Felix Wodaczek, Vittorio Del Tatto, Bingqing Cheng, Alessandro Laio

“…Abstract Feature selection is essential in the analysis of molecular systems and many other fields, but several uncertainties remain: What is the optimal number of features for a simplified, interpretable model that retains essential information? …”
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Adaptive Window Multi-Feature Fusion Point Cloud Semantic Segmentation Network by Lie Zhu

“…The method combines dynamic and fixed window feature extraction mechanisms, using dynamic windows to model global features and fixed windows to enhance local features, effectively improving segmentation accuracy and robustness. …”
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Thinking Styles Inventory: Psychometric features in college students from Buenos Aires by Agustín Freiberg Hoffmann, Fabiana Uriel, Rocío Fernández Da Lama, Mercedes Fernández Liporace

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Optimizing Mental Stress Detection via Heart Rate Variability Feature Selection by Mohsen Behradfar, Shotabdi Roy, Joseph Nuamah

“…These findings emphasize the value of targeted feature selection in optimizing stress detection models, particularly when handling high-dimensional datasets with potentially redundant features. …”
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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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Feature Extraction and Identification of Rheumatoid Nodules Using Advanced Image Processing Techniques by Azmath Mubeen, Uma N. Dulhare

“…A Hybrid CNN–Transformer model was employed for feature fusion, and feature selection and hyperparameter tuning were optimized using Gray Wolf Optimization (GWO) and Particle Swarm Optimization (PSO). …”
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Retracted: Target Recognition Method of Rehabilitation Robot Based on Image Local Features by Xing Li, Tianbao Wu

“…Firstly, after collecting or processing the initially prepared images, feature extraction is performed, and the feature vectors extracted from the features are classified and recognized and then transferred to the recognition model of the rehabilitation robot. …”
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Deep joint learning diagnosis of Alzheimer’s disease based on multimodal feature fusion by Jingru Wang, Shipeng Wen, Wenjie Liu, Xianglian Meng, Zhuqing Jiao

“…Moreover, a new deep joint learning diagnostic model was constructed to fully learn images features. …”
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A Deep Learning Method for Automatic Coronal Mass Ejection Feature Identification by P. Yang, H. S. Fu, J. B. Cao, F. Shen

“…Here, we present a deep learning–based algorithm for automated CME feature extraction, comprising four key stages: image preprocessing, segmentation, tracking, and feature extraction. …”
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Remote Sensing Surveillance Using Multilevel Feature Fusion and Deep Neural Network by Laiba Zahoor, Haifa F. Alhasson, Mohammed Alnusayri, Mohammed Alatiyyah, Dina Abdulaziz Alhammadi, Ahmad Jalal, Hui Liu

“…The extracted features are optimized by using quadratic discriminant analysis. …”
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Impacts of oxytactic microorganisms and viscous dissipation in Carreau nanoliquid featuring ferromagnetic nanoparticles by Muhammad Tabrez, I. Hussain, W.A. Khan, S.U. Khan, M. Waqas, Rzgar Farooq Rashid, M.I. Anwar, Mohamed Ben Ammar, Nurnadiah Zamri, Ruzimurod Abiyev, Hakim AL Garalleh

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