Showing 1 - 20 results of 64 for search '(( binary image path optimization algorithm ) OR ( binary base from optimization algorithm ))*', query time: 0.56s Refine Results
  1. 1

    A* Path-Finding Algorithm to Determine Cell Connections by Max Weng (22327159)

    Published 2025
    “…Pixel paths were classified using a z-score brightness threshold of 1.21, optimized for noise reduction and accuracy. …”
  2. 2

    MSE for ILSTM algorithm in binary classification. by Asmaa Ahmed Awad (16726315)

    Published 2023
    “…In this paper, a novel, and improved version of the Long Short-Term Memory (ILSTM) algorithm was proposed. The ILSTM is based on the novel integration of the chaotic butterfly optimization algorithm (CBOA) and particle swarm optimization (PSO) to improve the accuracy of the LSTM algorithm. …”
  3. 3

    Python-Based Algorithm for Estimating NRTL Model Parameters with UNIFAC Model Simulation Results by Se-Hee Jo (20554623)

    Published 2025
    “…A major challenge in bioprocess simulation is the lack of physical and chemical property databases for biochemicals. A Python-based algorithm was developed for estimating the nonrandom two-liquid (NRTL) model parameters of aqueous binary systems in a straightforward manner from simplified molecular-input line-entry specification (SMILES) strings of substances in a system. …”
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    Optimized Bayesian regularization-back propagation neural network using data-driven intrusion detection system in Internet of Things by Ashok Kumar K (21441108)

    Published 2025
    “…Hence, Binary Black Widow Optimization Algorithm (BBWOA) is proposed in this manuscript to improve the BRBPNN classifier that detects intrusion precisely. …”
  7. 7

    PathOlOgics_RBCs Python Scripts.zip by Ahmed Elsafty (16943883)

    Published 2023
    “…</p><p dir="ltr">In terms of classification, a second algorithm was developed and employed to preliminary sort or group the individual cells (after excluding the overlapping cells manually) into different categories using five geometric measurements applied to the extracted contour from each binary image mask (see PathOlOgics_script_2; preliminary shape measurements). …”
  8. 8

    Secure MANET routing with blockchain-enhanced latent encoder coupled GANs and BEPO optimization by Sandeep Jagonda Patil (22048337)

    Published 2025
    “…To tackle these challenges, this paper proposes the Blockchain Based Trusted Distributed Routing Scheme for MANET using Latent Encoder Coupled Generative Adversarial Network Optimized with Binary Emperor Penguin Optimizer (LEGAN-BEPO-BCMANET). …”
  9. 9

    Steps in the extraction of 14 coordinates from the CT slices for the curved MPR. by Linus Woitke (22783534)

    Published 2025
    “…Protruding paths are then eliminated using graph-based optimization algorithms, as demonstrated in f). …”
  10. 10

    Datasets and their properties. by Olaide N. Oyelade (14047002)

    Published 2023
    “…To address this, we proposed a novel hybrid binary optimization capable of effectively selecting features from increasingly high-dimensional datasets. …”
  11. 11

    Parameter settings. by Olaide N. Oyelade (14047002)

    Published 2023
    “…To address this, we proposed a novel hybrid binary optimization capable of effectively selecting features from increasingly high-dimensional datasets. …”
  12. 12

    Data_Sheet_1_A Global Optimizer for Nanoclusters.PDF by Maya Khatun (7437011)

    Published 2019
    “…This method is implemented in PyAR (https://github.com/anooplab/pyar) program. The global optimization in PyAR involves two parts, generation of several trial geometries and gradient-based local optimization of the trial geometries. …”
  13. 13

    <i>hi</i>PRS algorithm process flow. by Michela C. Massi (14599915)

    Published 2023
    “…From this dataset we can compute the MI between each interaction and the outcome and <b>(D)</b> obtain a ranked list (<i>I</i><sub><i>δ</i></sub>) based on this metric. …”
  14. 14

    SHAP bar plot. by Meng Cao (105914)

    Published 2025
    “…</p><p>Results</p><p>Logistic regression analysis identified age, hemoglobin concentration, education level, and social participation as significant factors influencing CI. Models based on NNET, RF, LR, and SVM algorithms were developed, achieving AUC of 0.918, 0.889, 0.872, and 0.760, respectively, on the test set. …”
  15. 15

    Sample screening flowchart. by Meng Cao (105914)

    Published 2025
    “…</p><p>Results</p><p>Logistic regression analysis identified age, hemoglobin concentration, education level, and social participation as significant factors influencing CI. Models based on NNET, RF, LR, and SVM algorithms were developed, achieving AUC of 0.918, 0.889, 0.872, and 0.760, respectively, on the test set. …”
  16. 16

    Descriptive statistics for variables. by Meng Cao (105914)

    Published 2025
    “…</p><p>Results</p><p>Logistic regression analysis identified age, hemoglobin concentration, education level, and social participation as significant factors influencing CI. Models based on NNET, RF, LR, and SVM algorithms were developed, achieving AUC of 0.918, 0.889, 0.872, and 0.760, respectively, on the test set. …”
  17. 17

    SHAP summary plot. by Meng Cao (105914)

    Published 2025
    “…</p><p>Results</p><p>Logistic regression analysis identified age, hemoglobin concentration, education level, and social participation as significant factors influencing CI. Models based on NNET, RF, LR, and SVM algorithms were developed, achieving AUC of 0.918, 0.889, 0.872, and 0.760, respectively, on the test set. …”
  18. 18

    ROC curves for the test set of four models. by Meng Cao (105914)

    Published 2025
    “…</p><p>Results</p><p>Logistic regression analysis identified age, hemoglobin concentration, education level, and social participation as significant factors influencing CI. Models based on NNET, RF, LR, and SVM algorithms were developed, achieving AUC of 0.918, 0.889, 0.872, and 0.760, respectively, on the test set. …”
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    Display of the web prediction interface. by Meng Cao (105914)

    Published 2025
    “…</p><p>Results</p><p>Logistic regression analysis identified age, hemoglobin concentration, education level, and social participation as significant factors influencing CI. Models based on NNET, RF, LR, and SVM algorithms were developed, achieving AUC of 0.918, 0.889, 0.872, and 0.760, respectively, on the test set. …”
  20. 20

    A new fast filtering algorithm for a 3D point cloud based on RGB-D information by Chaochuan Jia (7256237)

    Published 2019
    “…This method aligns the color image to the depth image, and the color mapping image is converted to an HSV image. Then, the optimal segmentation threshold of the V image that is calculated by using the Otsu algorithm is applied to segment the color mapping image into a binary image, which is used to extract the valid point cloud from the original point cloud with outliers. …”