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Showing 1 - 20 results of 187 for search '(((( data forest algorithm ) OR ( image processing algorithm ))) OR ( element method algorithm ))', query time: 0.13s Refine Results
  1. 1

    An image processing and genetic algorithm-based approach for the detection of melanoma in patients by Tokajian, Sima

    Published 2018
    “…In this paper, we present a twophase technique to classify images of lesions into benign or malignant. The first phase consists of an image processing-based method that extracts the Asymmetry, Border Irregularity, Color Variation and Diameter of a given mole. …”
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  2. 2

    Nonlinear analysis of shell structures using image processing and machine learning by M.S. Nashed (16392961)

    Published 2023
    “…<p dir="ltr">In this paper, we propose a novel approach to solve nonlinear stress analysis problems in shell structures using an image processing technique. In general, such problems in design optimisation or virtual reality applications must be solved repetitively in a short period using direct methods such as nonlinear finite element analysis. …”
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    Automatic image quality evaluation in digital radiography using for‐processing and for‐presentation images by Ioannis A. Tsalafoutas (14776939)

    Published 2024
    “…<h3>Purpose</h3><p dir="ltr">To investigate the impact of digital image post‐processing algorithms on various image quality (IQ) metrics of radiographic images under different exposure conditions.…”
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    A Survey of Audio Enhancement Algorithms for Music, Speech, Bioacoustics, Biomedical, Industrial, and Environmental Sounds by Image U-Net by Sania Gul (18272227)

    Published 2023
    “…Although, there are dedicated audio processing DNNs, yet, many recent models of AE have utilized U-Net: a DNN based on Convolutional Neural Network (CNN), fundamentally developed for image segmentation. …”
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    A Hybrid Intrusion Detection Model Using EGA-PSO and Improved Random Forest Method by Amit Kumar Balyan (18288964)

    Published 2022
    “…Due to a limited training dataset, an ML-based IDS generates a higher false detection ratio and encounters data imbalance issues. To deal with the data-imbalance issue, this research develops an efficient hybrid network-based IDS model (HNIDS), which is utilized using the enhanced genetic algorithm and particle swarm optimization(EGA-PSO) and improved random forest (IRF) methods. …”
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    Differential Evolution and Its Applications in Image Processing Problems: A Comprehensive Review by Chakraborty, Sanjoy

    Published 2022
    “…It also summarizes the problems solved in image processing by DE and its variants.…”
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    Predict Student Success and Performance factors by analyzing educational data using data mining techniques by ATIF, MUHAMMAD

    Published 2022
    “…The research study is performed as experimental analysis and develop models from nine machine learning algorithms including KNN, Naïve Bayes, SVM, Logistic regression, Decision Tree, Random forest, Adaboost, Bagging Classifier, and voting Classifier. …”
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  17. 17

    A Novel Partitioned Random Forest Method-Based Facial Emotion Recognition by Hanif Heidari (22467148)

    Published 2025
    “…A range of machine learning (ML) methods can be used to recognize facial expressions based on data from small to large datasets. Random Forest (RF) is simpler and more efficient than other ML algorithms. …”
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    Random Forest Bagging and X‐Means Clustered Antipattern Detection from SQL Query Log for Accessing Secure Mobile Data by Rajesh Kumar Dhanaraj (19646269)

    Published 2021
    “…<p dir="ltr">In the current ongoing crisis, people mostly rely on mobile phones for all the activities, but query analysis and mobile data security are major issues. Several research works have been made on efficient detection of antipatterns for minimizing the complexity of query analysis. …”
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    A Novel Big Data Classification Technique for Healthcare Application Using Support Vector Machine, Random Forest and J48 by Al-Manaseer, Hitham

    Published 2022
    “…This was done by studying the performance of three well-known classification algorithms Random Forest Classifier (RFC), Support Vector Machine (SVM), and Decision Tree-J48 (J48), to predict the probability of heart attack. …”
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