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  1. 261

    BBDetector: Intelligent border binary detection in IoT device firmware based on a multidimensional feature model. by Shudan Yue, Guimin Zhang, Qingbao Li, Wenbo Zhang, Xiaonan Li, Weihua Jiao

    Published 2025-01-01
    “…In the field of firmware security analysis for Internet of Things (IoT) devices, border binary detection has become an important research focus. …”
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    Article
  2. 262

    Concrete Crack Detection and Segregation: A Feature Fusion, Crack Isolation, and Explainable AI-Based Approach by Reshma Ahmed Swarna, Muhammad Minoar Hossain, Mst. Rokeya Khatun, Mohammad Motiur Rahman, Arslan Munir

    Published 2024-08-01
    “…This research introduces a novel feature fusion approach that enhances crack detection accuracy and interpretability. …”
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    Article
  3. 263

    A Prediction-Based Anomaly Detection Method for Traffic Flow Data with Multi-Domain Feature Extraction by Xianguang Jia, Jie Qu, Yingying Lyu, Mengyi Guo, Jinke Zhang, Fengxiang Guo

    Published 2025-03-01
    “…Additionally, anomaly detection accuracy is often limited by insufficient prediction error analysis. …”
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    Article
  4. 264
  5. 265

    Sea Surface Floating Small-Target Detection Based on Dual-Feature Images and Improved MobileViT by Yang Liu, Hongyan Xing, Tianhao Hou

    Published 2025-03-01
    “…This study addresses the challenge of weak feature representation in one-dimensional (1D) sea clutter time-series analysis and suboptimal detection performance for sea surface small targets. …”
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    Article
  6. 266
  7. 267

    Advanced feature fusion of radiomics and deep learning for accurate detection of wrist fractures on X-ray images by Mohamed J. Saadh, Qusay Mohammed Hussain, Rafid Jihad Albadr, Hardik Doshi, M. M. Rekha, Mayank Kundlas, Amrita Pal, Jasur Rizaev, Waam Mohammed Taher, Mariem Alwan, Mahmod Jasem Jawad, Ali M. Ali Al-Nuaimi, Bagher Farhood

    Published 2025-05-01
    “…Feature selection methods, including ANOVA, Mutual Information (MI), Principal Component Analysis (PCA), and Recursive Feature Elimination (RFE), were applied to optimize the feature set. …”
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    Article
  8. 268

    MTAD-TF: Multivariate Time Series Anomaly Detection Using the Combination of Temporal Pattern and Feature Pattern by Q. He, Y. J. Zheng, C.L. Zhang, H. Y. Wang

    Published 2020-01-01
    “…Our article proposes an unsupervised multivariate time series anomaly detection. In the prediction part, multiscale convolution and graph attention network are mainly used to capture information in temporal pattern with feature pattern. …”
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    Article
  9. 269

    Advanced Phishing Detection: Leveraging t-SNE Feature Extraction and Machine Learning on a Comprehensive URL Dataset by Taha Etem, Mustafa Teke

    Published 2024-12-01
    “…The proposed dataset comprises 134,850 legitimate URLs and 100,945 phishing URLs, providing a robust foundation for analysis. We applied the t-SNE technique for feature extraction, condensing the original 51 features into only 2, while preserving high detection accuracy. …”
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    Article
  10. 270

    Improving detection of Parkinson’s disease with acoustic feature optimization using particle swarm optimization and machine learning by Elmoundher Hadjaidji, Mohamed Cherif Amara Korba, Khaled Khelil

    Published 2025-01-01
    “…Parkinson’s disease (PD), characterized by motor impairments and tremors, also presents early-stage vocal abnormalities that hold diagnostic potential. Leveraging voice analysis and classification techniques, numerous studies explore the feasibility of early PD detection through automated systems. …”
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    Article
  11. 271
  12. 272

    Kidney Ensemble-Net: Enhancing Renal Carcinoma Detection Through Probabilistic Feature Selection and Ensemble Learning by Zaib Akram, Kashif Munir, Muhammad Usama Tanveer, Atiq Ur Rehman, Amine Bermak

    Published 2024-01-01
    “…These extracted features are then transferred into a refined probabilistic feature set, upon which we construct an ensemble model leveraging the strengths of Logistic Regression (LR), Random Forest (RF), and Gaussian Naive Bayes (GNB) classifiers. …”
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    Article
  13. 273

    Real-Time Landform Feature Detection and Segmentation Based on Heterogeneous MPSoCs for Lunar Robotic Exploration by Q. Fan, R. Duan, B. Wu, H. Zhou, S. Zhang, Y. Ma

    Published 2025-07-01
    “…In this paper, we present neural network inference accelerators using Vitis-AI on an FPGA heterogeneous MPSoC for lunar landform analysis, including landform feature detection and segmentation. …”
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    Article
  14. 274

    Failure Detection of Laser Welding Seam for Electric Automotive Brake Joints Based on Image Feature Extraction by Diqing Fan, Chenjiang Yu, Ling Sha, Haifeng Zhang, Xintian Liu

    Published 2025-07-01
    “…Laser-welded automotive brake joints are subjected to weld defect detection and classification, and image processing algorithms are optimized to improve the accuracy of detection and failure analysis by utilizing the high efficiency, low cost, flexibility, and automation advantages of machine vision technology. …”
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    Article
  15. 275

    Comparison of Linear and Nonlinear Features of Electroencephalogram to Classify Alcoholic and Non-Alcoholic People by Elizabeth Stewart, Owen Kelly

    Published 2024-06-01
    “…After EEG preprocessing, spectral analysis was done to calculate linear features. Then, some nonlinear features were calculated through fractal dimension, entropy analysis, Hurst exponent, Lempel-Ziv complexity, and detrended fluctuation analysis. …”
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  16. 276

    The abnormal traffic detection scheme based on PCA and SSH by Zhenhui Wang, Dezhi Han, Ming Li, Han Liu, Mingming Cui

    Published 2022-12-01
    “…At the same time, PCSS also combines feature fusion and SSH to enhance the feature extraction of unclear features data, and effectively improve the detection speed and accuracy. …”
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    Article
  17. 277
  18. 278

    DDA-MSLD: A Multi-Feature Speech Lie Detection Algorithm Based on a Dual-Stream Deep Architecture by Pengfei Guo, Shucheng Huang, Mingxing Li

    Published 2025-05-01
    “…This combination enables the network to more comprehensively capture the context of speech signals and focus on the parts that are more critical for lie detection. It can perform in-depth sequence pattern analysis on manually extracted static prosodic features and nonlinear dynamic features, obtaining high-order dynamic features related to lies. …”
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    Article
  19. 279

    Quantitative pleural line characterization outperforms traditional lung texture ultrasound features in detection of COVID‐19 by Laith R. Sultan, Yale Tung Chen, Theodore W. Cary, Khalid Ashi, Chandra M. Sehgal

    Published 2021-04-01
    “…The diagnostic performance of the 2 feature sets was measured and compared using receiver operating characteristics curve analysis. …”
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  20. 280