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phase optimization » whale optimization (Expand Search), based optimization (Expand Search), path optimization (Expand Search)
changes phase » chances phase (Expand Search), changes have (Expand Search), changes made (Expand Search)
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Showing 1 - 10 results of 10 for search '(( binary changes phase optimization algorithm ) OR ( binary image global optimization algorithm ))', query time: 0.48s Refine Results
  1. 1
    The confidence curve of a binary image.

    The confidence curve of a binary image. by Dingming Yang (8505990)

    Published 2022
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  2. 2
    The confidence change of the binary image after iteration.

    The confidence change of the binary image after iteration. by Dingming Yang (8505990)

    Published 2022
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  3. 3
    Illustration of the transformed binary images of normal, benign, and malignant samples into grayscale.

    Illustration of the transformed binary images of normal, benign, and malignant samples into grayscale. by Tehnan I. A. Mohamed (16846175)

    Published 2023
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  4. 4
    Image1_Applying the Hubbard-Stratonovich Transformation to Solve Scheduling Problems Under Inequality Constraints With Quantum Annealing.TIF

    Image1_Applying the Hubbard-Stratonovich Transformation to Solve Scheduling Problems Under Inequality Constraints With Quantum Annealing.TIF by Sizhuo Yu (11429743)

    Published 2021
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  5. 5
    Image3_Applying the Hubbard-Stratonovich Transformation to Solve Scheduling Problems Under Inequality Constraints With Quantum Annealing.TIF

    Image3_Applying the Hubbard-Stratonovich Transformation to Solve Scheduling Problems Under Inequality Constraints With Quantum Annealing.TIF by Sizhuo Yu (11429743)

    Published 2021
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  6. 6
    Image2_Applying the Hubbard-Stratonovich Transformation to Solve Scheduling Problems Under Inequality Constraints With Quantum Annealing.TIF

    Image2_Applying the Hubbard-Stratonovich Transformation to Solve Scheduling Problems Under Inequality Constraints With Quantum Annealing.TIF by Sizhuo Yu (11429743)

    Published 2021
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  7. 7
    Generalized Tensor Decomposition With Features on Multiple Modes

    Generalized Tensor Decomposition With Features on Multiple Modes by Jiaxin Hu (1327875)

    Published 2021
    “…An efficient alternating optimization algorithm with provable spectral initialization is further developed. …”
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  8. 8
    Thesis-RAMIS-Figs_Slides

    Thesis-RAMIS-Figs_Slides by Felipe Santibañez-Leal (10967991)

    Published 2024
    “…<br><br>Finally, although the developed concepts, ideas and algorithms have been developed for inverse problems in geostatistics, the results are applicable to a wide range of disciplines where similar sampling problems need to be faced, included but not limited to design of communication networks, optimal integration and communication of swarms of robots and drones, remote sensing.…”
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  9. 9
    Data Sheet 1_Detection of litchi fruit maturity states based on unmanned aerial vehicle remote sensing and improved YOLOv8 model.docx

    Data Sheet 1_Detection of litchi fruit maturity states based on unmanned aerial vehicle remote sensing and improved YOLOv8 model.docx by Changjiang Liang (21099887)

    Published 2025
    “…The results showed significant stage-based changes in the maturity states of litchi fruits: during the rapid growth phase, the fruit count increased by 18.28%; during the maturity differentiation phase, semi-mature fruits accounted for approximately 53%; and during the peak maturity phase, mature fruits exceeded 50%, with a fruit drop rate of 11.46%. …”
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  10. 10
    Data_Sheet_1_Alzheimer’s Disease Diagnosis and Biomarker Analysis Using Resting-State Functional MRI Functional Brain Network With Multi-Measures Features and Hippocampal Subfield and Amygdala Volume of Structural MRI.pdf

    Data_Sheet_1_Alzheimer’s Disease Diagnosis and Biomarker Analysis Using Resting-State Functional MRI Functional Brain Network With Multi-Measures Features and Hippocampal Subfield... by Uttam Khatri (12689072)

    Published 2022
    “…Finally, we implemented and compared the different feature selection algorithms to integrate the structural features, brain networks, and voxel features to optimize the diagnostic identifications of AD using support vector machine (SVM) classifiers. …”
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