Showing 641 - 660 results of 2,992 for search '((\ sources selection function\ ) OR (( source OR resources) detection functions\ ))', query time: 0.37s Refine Results
  1. 641

    F-OSFA: A Fog Level Generalizable Solution for Zero-Day DDOS Attacks Detection by Muhammad Rashid Minhas, Qaisar M. Shafi, Shoab Ahmed Khan, Tahir Ahmad, Subhan Ullah, Attaullah Buriro, Muhammad Azfar Yaqub

    Published 2025-01-01
    “…The third component is a signature-based resource usage analyzer to counter attacks mimicking normal traffic. …”
    Get full text
    Article
  2. 642

    Automated Artery Detection and Stenosis Classification in CTA Using Deep Learning for Peripheral Arterial Disease by Ali M. O. A. Anwer, Hacer Karacan, Muhammed Rabee, Levent Enver, Gonca Cabuk

    Published 2025-01-01
    “…We use Faster R-CNN with a ResNet-101 backbone driven by a custom loss function to achieve good artery localization and reduce false positives. …”
    Get full text
    Article
  3. 643
  4. 644

    GastroEndoNet: Comprehensive endoscopy image dataset for GERD and polyp detectionMendeley Data by Abu Kowshir Bitto, Md. Hasan Imam Bijoy, Kamrul Hassan Shakil, Aka Das, Khalid Been Badruzzaman Biplob, Imran Mahmud, Syed Md. Minhaz Hossain

    Published 2025-06-01
    “…It provides an invaluable resource for developing machine learning models aimed at the automatic diagnosis, classification, and detection of GERD and polyps, potentially improving the speed and accuracy of clinical decision-making. …”
    Get full text
    Article
  5. 645
  6. 646

    Estimating Leaf Chlorophyll Fluorescence Parameters Using Partial Least Squares Regression with Fractional-Order Derivative Spectra and Effective Feature Selection by Jie Zhuang, Quan Wang

    Published 2025-02-01
    “…Chlorophyll fluorescence (ChlF) parameters serve as non-destructive indicators of vegetation photosynthetic function and are widely used as key input parameters in photosynthesis–fluorescence models. …”
    Get full text
    Article
  7. 647
  8. 648
  9. 649

    A Heterogeneity-Aware Semi-Decentralized Model for a Lightweight Intrusion Detection System for IoT Networks Based on Federated Learning and BiLSTM by Shuroog Alsaleh, Mohamed El Bachir Menai, Saad Al-Ahmadi

    Published 2025-02-01
    “…Most IoT devices have limited resource capabilities (e.g., memory capacity, processing power, and energy consumption) to function as conventional intrusion detection systems (IDSs). …”
    Get full text
    Article
  10. 650

    Enhancing Human Detection in Occlusion-Heavy Disaster Scenarios: A Visibility-Enhanced DINO (VE-DINO) Model with Reassembled Occlusion Dataset by Zi-An Zhao, Shidan Wang, Min-Xin Chen, Ye-Jiao Mao, Andy Chi-Ho Chan, Derek Ka-Hei Lai, Duo Wai-Chi Wong, James Chung-Wai Cheung

    Published 2025-01-01
    “…VE-DINO enhances detection accuracy by incorporating body part key point information and employing a specialized loss function. …”
    Get full text
    Article
  11. 651
  12. 652

    Lightweight coal miners and manned vehicles detection model based on deep learning and model compression techniques: A case study of coal mines in Guizhou region by Beijing XIE, Heng LI, Zheng LUAN, Zhen LEI, Xiaoxu LI, Zhuo LI

    Published 2025-02-01
    “…Compared to various lightweight architectures and advanced detection models, this method demonstrates excellent accuracy, lower computational costs, and better real-time performance, providing a feasible coal mine pedestrian-vehicle detection method for resource-constrained coal mine scenarios, meeting the deployment requirements of coal mine video surveillance and enabling real-time alerts for intelligent inspection of coal mine pedestrian-vehicles.…”
    Get full text
    Article
  13. 653

    Source Process Estimation for the 2024 Mw 7.1 Hyuganada, Japan, Earthquake and Forward Modeling Using N‐net Ocean Bottom Seismometer Data by R. Shibata, H. Kubo, W. Suzuki, S. Aoi, H. Sekiguchi

    Published 2025-05-01
    “…The N‐net seafloor seismograms of the mainshock with a frequency of ∼0.05 Hz recorded east of the source area were reproduced for several stations using the empirical Green's function approach based on the estimated source process data.…”
    Get full text
    Article
  14. 654
  15. 655
  16. 656

    Ibai mag blinds blindana tiuhan? (Luke 6,39). Pragmatic functions and syntactic strategies in the Gothic left sentence periphery by Marina Buzzoni

    Published 2025-01-01
    “…The interference role of the Greek and Latin source texts will also be taken into consideration, mainly in order to ascertain whether the grammaticalization processes which those elements underwent were either induced or implemented by the models. …”
    Get full text
    Article
  17. 657

    Ibai mag blinds blindana tiuhan? (Luke 6,39). Pragmatic functions and syntactic strategies in the Gothic left sentence periphery by Marina Buzzoni

    Published 2025-01-01
    “…The interference role of the Greek and Latin source texts will also be taken into consideration, mainly in order to ascertain whether the grammaticalization processes which those elements underwent were either induced or implemented by the models. …”
    Get full text
    Article
  18. 658

    Arlclustering: an R package for community detection in social networks based on user interaction and association rule learning by Mohamed El-Moussaoui, Mohamed Hanine, Ali Kartit, Tarik Agouti

    Published 2025-07-01
    “…Abstract ARLClustering is an open-source R package for community detection in social networks. …”
    Get full text
    Article
  19. 659
  20. 660

    A METHOD FOR INVESTIGATING MACHINE LEARNING ATTACKS ON ARBITER-TYPE PHYSICALLY UNCLONABLE FUNCTIONS by Yuri A. Korotaev

    Published 2025-02-01
    “…This approach allows for a preliminary evaluation of the effectiveness of different algorithms for attacking APUFs without access to challenge-response datasets from real instances of physically unclonable functions. Attacks were conducted on models of basic and modified variants of APUFs from the open-source library "pypuf", using classical logistic regression and artificial neural networks (ANNs). …”
    Get full text
    Article