Search alternatives:
sample detection » early detection (Expand Search), image detection (Expand Search)
Showing 1 - 20 results of 46 for search '(( sample selection algorithm ) OR ( sample detection algorithm ))', query time: 0.11s Refine Results
  1. 1
  2. 2

    A Hybrid Intrusion Detection Model Using EGA-PSO and Improved Random Forest Method by Amit Kumar Balyan (18288964)

    Published 2022
    “…In the initial phase, the proposed HNIDS utilizes hybrid EGA-PSO methods to enhance the minor data samples and thus produce a balanced data set to learn the sample attributes of small samples more accurately. …”
  3. 3

    Sample intelligence-based progressive hedging algorithms for the stochastic capacitated reliable facility location problem by Nezir Aydin (8355378)

    Published 2024
    “…Two commonly used SP methods are approximation methods, i.e., Sample Average Approximation (SAA), and decomposition methods, i.e., Progressive Hedging Algorithm (PHA). …”
  4. 4

    Novel Peak Detection Algorithms for Pileup Minimization in Gamma Ray Spectroscopy by Raad, M.W.

    Published 2006
    “…Gamma pulses from a 3" Na(TI) scintillation detector were captured as single and double pulses for the purpose of testing the peak detection algorithms. The pulse classification technique was tested successfully on a TMS320C6000 high performance floating-point processor yielding a reduction of the execution time to 2 msec…”
    Get full text
    Get full text
    article
  5. 5

    Enhanced PSO-Based NN for Failures Detection in Uncertain Wind Energy Systems by Khaled Dhibi (16891524)

    Published 2023
    “…Therefore, an enhanced particle swarm optimization (PSO), data reduction, and interval-valued representation are proposed. First, a feature selection tool using PSO Algorithm is developed. Then, in order to maximize the diversity between data samples and improve the effectiveness of using PSO algorithm for feature selection, the Euclidean distance metric is used in order to reduce the data and maximize the diversity between data samples. …”
  6. 6

    Machine Learning-Driven Prediction of Corrosion Inhibitor Efficiency: Emerging Algorithms, Challenges, and Future Outlooks by Najam Us Sahar Riyaz (22927843)

    Published 2025
    “…At the same time, virtual sample augmentation and genetic algorithm feature selection elevate sparse data performance, raising k-nearest neighbor models from R<sup>2</sup> = 0.05 to 0.99 in a representative thiophene set. …”
  7. 7

    Interval-Valued SVM Based ABO for Fault Detection and Diagnosis of Wind Energy Conversion Systems by Majdi Mansouri (16869885)

    Published 2022
    “…The proposed improved ABO method consists in reducing the number of samples in the training data set using the Euclidean distance and extracting the most significant features from the reduced data using ABO algorithm. …”
  8. 8

    Application of updated joint detection algorithm for the analysis of drilling parameters of roof bolters in multiple joints conditions by Liu, Wenpeng

    Published 2017
    “…This paper reviews testing procedures, data analysis, updated algorithms used for joint detection, and discusses the latest round of testing in samples with simulated joints at various angles along the borehole.…”
    Get full text
    Get full text
    Get full text
    conferenceObject
  9. 9
  10. 10
  11. 11
  12. 12
  13. 13

    Data mining approach to predict student's selection of program majors by SIDDARTHA, SHARMILA

    Published 2019
    “…The purpose of this study is to develop a data mining approach for predicting student's selection of program majors. The approach includes a methodology to manage data mining projects, sampling techniques to handle imbalanced data and multiclass data, a set of classification algorithms to predict and measures to evaluate performance of models. …”
    Get full text
  14. 14

    Parallel Algorithm for Hardware Implementation of Inverse Halftoning by Siddiqi, Umair F.

    Published 2005
    “…The 15-pixel parallel version of the algorithm was tested on sample images and a simple and effective method has been used to overcome quality degradation due to pixel loss in the proposed algorithm. …”
    Get full text
    article
  15. 15

    Parallel algorithm for hardware implementation of inverse halftoning by Siddiqi, U.F.

    Published 2005
    “…The 15-pixel parallel version of the algorithm was tested on sample images and a simple and effective method has been used to overcome quality degradation due to pixel loss in the proposed algorithm. …”
    Get full text
    Get full text
    article
  16. 16

    Gene selection for microarray data classification based on Gray Wolf Optimizer enhanced with TRIZ-inspired operators by Abu Zitar, Raed

    Published 2021
    “…Pattern recognition algorithms are widely applied to gene expression data to differentiate between health and cancerous patient samples. …”
    Get full text
  17. 17

    VEGAWES: variational segmentation on whole exome sequencing for copy number detection by Samreen Anjum (19651882)

    Published 2015
    “…We tested this algorithm on synthetic data and 100 Glioblastoma Multiforme primary tumor samples. …”
  18. 18

    Power System Transient Stability Assessment Based on Machine Learning Algorithms and Grid Topology by Senyuk, Mihail

    Published 2023
    “…In this study, the emergency control algorithms based on ensemble machine learning algorithms (XGBoost and Random Forest) were developed for a low-inertia power system. …”
    Get full text
    article
  19. 19

    Novel Multi Center and Threshold Ternary Pattern Based Method for Disease Detection Method Using Voice by Turker Tuncer (16677966)

    Published 2020
    “…A more compact multileveled features are then obtained by sample-based discretization techniques and Neighborhood Component Analysis (NCA) is applied to select features iteratively. …”
  20. 20

    Diagnostic performance of artificial intelligence in detecting and subtyping pediatric medulloblastoma from histopathological images: A systematic review by Hiba Alzoubi (18001609)

    Published 2025
    “…</p><h3>Conclusion</h3><p dir="ltr">AI algorithms show promise in detecting and subtyping medulloblastomas, but the findings are limited by overreliance on one dataset, small sample sizes, limited study numbers, and lack of meta-analysis Future research should develop larger, more diverse datasets and explore advanced approaches like deep learning and foundation models. …”