Showing 981 - 1,000 results of 2,064 for search 'network evaluation (pattern OR patterns)', query time: 0.13s Refine Results
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    Microstructural integrity of autonomic central nervous tracts is linked to cardiovascular health by Janis M. Nolde, Alexander Rau, Elias Kellner, Horst Urbach, Cornelius Weiller, Fabian Bamberg, Jakob Weiss, Marco Reisert, Jonas A. Hosp

    Published 2025-08-01
    “…Introduction: The central autonomic network (CAN), which controls sympathetic and parasympathetic activity, plays a central role in the pathogenesis of cardiovascular disease and serves as a target for therapeutic approaches. …”
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    Article
  4. 984

    Classification of musculoskeletal pain using machine learning by Dalia Mohamed Fouad, Marwa Mahmoud Mahfouz, Mohammed Mostafa Mohamed, Mahmoud Yassin Elzanaty, Tarek Abd El-Hafeez

    Published 2025-07-01
    “…By integrating PSO with neural networks, this framework aims to enhance the detection of pain risk patterns, offering insights into the interplay between various factors and musculoskeletal health. …”
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    Article
  5. 985

    Motor imagery EEG signal classification using novel deep learning algorithm by Sathish Mathiyazhagan, M. S. Geetha Devasena

    Published 2025-07-01
    “…For spatial feature enhancement the proposed approach utilizes source power coherence (SPoC) integrated with common spatial patterns (CSP) for robust feature extraction. For final feature classification, an adaptive deep belief network (ADBN) is proposed. …”
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    Article
  6. 986

    An Evolutionary Deep Reinforcement Learning-Based Framework for Efficient Anomaly Detection in Smart Power Distribution Grids by Mohammad Mehdi Sharifi Nevisi, Mehrdad Shoeibi, Francisco Hernando-Gallego, Diego Martín, Sarvenaz Sadat Khatami

    Published 2025-05-01
    “…To address these challenges, this study proposes a novel deep reinforcement learning (DRL)-based framework, integrating a convolutional neural network (CNN) for hierarchical feature extraction and a recurrent neural network (RNN) for sequential pattern recognition and time-series modeling. …”
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    OXSeg: Multidimensional Attention UNet-Based Lip Segmentation Using Semi-Supervised Lip Contours by Hanie Moghaddasi, Christina Chambers, Sarah N. Mattson, Jeffrey R. Wozniak, Claire D. Coles, Raja Mukherjee, Michael Suttie

    Published 2025-01-01
    “…We unravel the micro-patterns in facial images using local binary patterns to build multidimensional inputs. …”
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  9. 989

    NeuroFuzDetect–A Neural and Fuzzy Inference System for Fake News Classification by Borra Vineetha, Munirathinam Nirmala

    Published 2025-01-01
    “…NeuroFuzDetect leverages advanced computational reasoning to analyze uncertainty and ambiguity in textual data by evaluating critical linguistic features, including credibility, emotional tone, and language patterns, ensuring interpretability by providing justifications for its predictions. …”
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  10. 990

    The Comparison of Activation Functions in Feature Extraction Layer using Sharpen Filter by Oktavia Citra Resmi Rachmawati, Ali Ridho Barakbah, Tita Karlita

    Published 2025-06-01
    “… Activation functions are a critical component in the feature extraction layer of deep learning models, influencing their ability to identify patterns and extract meaningful features from input data. …”
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    A Global Deep Learning Perspective on Australia-Wide Monthly Precipitation Prediction by Luyi Shen, Guoqi Qian, Antoinette Tordesillas

    Published 2024-07-01
    “…Gaining a deep understanding of precipitation patterns is beneficial for enhancing Australia’s adaptability to climate change. …”
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  12. 992

    GraphFedAI framework for DDoS attack detection in IoT systems using federated learning and graph based artificial intelligence by Mohd Anjum, Ashit Kumar Dutta, Ali Elrashidi, Sana Shahab, Asma Aldrees, Zaffar Ahmed Shaikh, Abeer Aljohani

    Published 2025-08-01
    “…To address these limitations, this research proposes GraphFedAI, a novel framework that integrates adaptive session-based graph modeling, Pearson correlation-guided feature selection, interpolation-aware graph neural network (GNN) training, and federated learning to enable robust, scalable, and privacy-preserving DDoS detection in heterogeneous Internet of Things (IoT) networks.The framework represents the IoT network as dynamic graphs where communication patterns among devices are modeled as edges that evolve over time. …”
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    Smart adaptive learning and optimized feature clustering for enhanced image retrieval by P. Umaeswari, Sujata Patil, Parameshachari Bidare Divakarachari, Przemysław Falkowski-Gilski

    Published 2025-07-01
    “…CBIR extracts key features related to texture, shape, and color using techniques such as Local Binary Pattern, Zernike Moments, and Color Moments. Additionally, an Entropy-based Divergence (ED) function is incorporated into a Convolutional Neural Network (CNN) named EDCNN to improve matching accuracy by reducing redundant activation in hidden layers. …”
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    Selecting Observationally Constrained Global Climate Model Ensembles Using Autoencoders and Transfer Learning by Chibuike Chiedozie Ibebuchi, Oluwaferanmi Akinyemi, Itohan‐Osa Abu

    Published 2025-03-01
    “…These results highlight the effectiveness of neural network techniques in evaluating and ranking GCMs for model intercomparison projects.…”
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    Identification of Candidate Genes for Soybean Storability via GWAS and WGCNA Approaches by Xu Wu, Yuhe Wang, Jiapei Xie, Zhenhong Yang, Haiyan Li, Yongguang Li, Weili Teng, Xue Zhao, Yuhang Zhan, Yingpeng Han

    Published 2024-10-01
    “…Through the analysis of expression patterns, two candidate genes (<i>Glyma.03G058300</i>, <i>Glyma.16G074600</i>) potentially involved in seed storage tolerance were ultimately identified. …”
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    Hybrid AI for Predictive Cyber Risk Assessment: Federated Graph-Transformer Architecture With Explainability by Jaime Govea, Rommel Gutierrez, William Villegas-Ch, Alexandra Maldonado Navarro

    Published 2025-01-01
    “…The model was trained and evaluated using public datasets (CIC-IDS2017, UNSW-NB15, MITRE ATT&#x0026;CK, TON_IoT) and synthetically generated traffic from honeypots and real anonymized networks. …”
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