Showing 121 - 140 results of 727 for search '(((((( time decrease ) OR ( deep increase ))) OR ( peer decrease ))) OR ( mean decrease ))*', query time: 0.12s Refine Results
  1. 121

    Communication-efficient hierarchical federated learning for IoT heterogeneous systems with imbalanced data by Alaa Awad Abdellatif (17151163)

    Published 2022
    “…<p dir="ltr">Federated Learning (FL) is a distributed learning methodology that allows multiple nodes to cooperatively train a deep learning model, without the need to share their local data. …”
  2. 122

    Human Action Recognition: A Taxonomy-Based Survey, Updates, and Opportunities by Md Golam Morshed (19420537)

    Published 2023
    “…One of the most challenging issues for computer vision is the automatic and precise identification of human activities. A significant increase in feature learning-based representations for action recognition has emerged in recent years, due to the widespread use of deep learning-based features. …”
  3. 123

    Evaluating machine learning technologies for food computing from a data set perspective by Nauman Ullah Gilal (17302714)

    Published 2023
    “…Food computing benefits from technologies based on modern machine learning techniques, including deep learning, deep convolutional neural networks, and transfer learning. …”
  4. 124

    A systematic review and meta-analysis on the impact of early vs. delayed pharmacological thromboprophylaxis in patients with traumatic brain injury by Muhammad Hamza Shuja (19748620)

    Published 2024
    “…Our findings indicated that early prophylaxis significantly reduced the incidence of VTE, deep vein thrombosis (DVT), pulmonary embolism (PE), and overall mortality when compared to late administration. …”
  5. 125

    A New Flow-Based Approach for Enhancing Botnet Detection Efficiency Using Convolutional Neural Networks and Long Short-Term Memory by Mehdi Asadi (12566741)

    Published 2025
    “…<p dir="ltr">Despite the growing research and development of botnet detection tools, an ever-increasing spread of botnets and their victims is being witnessed. …”
  6. 126

    Food fraud detection using explainable artificial intelligence by Okan Buyuktepe (17991493)

    Published 2023
    “…<div><p>Recently, the global food supply chain has become increasingly complex, and its scalability has grown. …”
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    TB-CXRNet: Tuberculosis and Drug-Resistant Tuberculosis Detection Technique Using Chest X-ray Images by Tawsifur Rahman (14150523)

    Published 2024
    “…Moreover, due to the increase of drug-resistant tuberculosis, the disease becomes more challenging in recent years. …”
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    Improving diagnosis and prognosis of lung cancer using vision transformers: a scoping review by Hazrat Ali (421019)

    Published 2023
    “…It provides key insights into how vision transformers complemented the performance of AI and deep learning methods for lung cancer. Furthermore, the review also identifies the datasets that contributed to advancing the field.…”
  12. 132

    Detection of Real-Time Malicious Intrusions and Attacks in IoT Empowered Cybersecurity Infrastructures by Irfan Ali Kandhro (17541876)

    Published 2023
    “…To address these issues, we propose a deep learning-based novel method to detect cybersecurity vulnerabilities and breaches in cyber-physical systems. …”
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    Identifying Regional Trends in Avatar Customization by Peter Mawhorter (18602944)

    Published 2019
    “…We find that avatar customization correlates with increased social activity, and we are able to identify distinct visual trends among the U.S.…”
  16. 136

    Exploring Effects of Mental Stress with Data Augmentation and Classification Using fNIRS by Khan, Malik Nasir Afzal

    Published 2025
    “…To improve our results and increase our dataset, we use data augmentation with a deep convolutional generative adversarial network (DCGAN). …”
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  17. 137

    YOLO-SAIL: Attention-Enhanced YOLOv5 With Optimized Bi-FPN for Ship Target Detection in SAR Images by Prabu Selvam (22330264)

    Published 2025
    “…It has recently become increasingly popular to apply deep learning algorithms to the identification of ships in SAR images. …”
  18. 138

    Hyperspectral-physiological based predictive model for transpiration in greenhouses under CO<sub>2</sub> enrichment by Ikhlas Ghiat (16932564)

    Published 2023
    “…Three machine learning models were investigated for transpiration modelling and prediction: deep neural networks (DNN), extreme gradient boosting (XGBoost), and support vector machine regression (SVR). …”
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