يعرض 1 - 20 نتائج من 23 نتيجة بحث عن '(( lens based case optimization algorithm ) OR ( binary image design optimization algorithm ))', وقت الاستعلام: 0.46s تنقيح النتائج
  1. 1

    Lens imaging opposition-based learning. حسب Yuqi Xiong (12343771)

    منشور في 2025
    "…The algorithm integrates three key strategies: a precise population elimination strategy, which optimizes the population structure by eliminating individuals with low fitness and intelligently generating new ones; a lens imaging-based opposition learning strategy, which expands the exploration of the solution space through reflection and scaling to reduce the risk of local optima; and a boundary control strategy based on the best individual, which effectively constrains the search range to avoid inefficient searches and premature convergence. …"
  2. 2
  3. 3

    Compare algorithm parameter settings. حسب Yuqi Xiong (12343771)

    منشور في 2025
    "…The algorithm integrates three key strategies: a precise population elimination strategy, which optimizes the population structure by eliminating individuals with low fitness and intelligently generating new ones; a lens imaging-based opposition learning strategy, which expands the exploration of the solution space through reflection and scaling to reduce the risk of local optima; and a boundary control strategy based on the best individual, which effectively constrains the search range to avoid inefficient searches and premature convergence. …"
  4. 4
  5. 5
  6. 6

    -value on CEC2022 (dim = 20). حسب Yuqi Xiong (12343771)

    منشور في 2025
    "…The algorithm integrates three key strategies: a precise population elimination strategy, which optimizes the population structure by eliminating individuals with low fitness and intelligently generating new ones; a lens imaging-based opposition learning strategy, which expands the exploration of the solution space through reflection and scaling to reduce the risk of local optima; and a boundary control strategy based on the best individual, which effectively constrains the search range to avoid inefficient searches and premature convergence. …"
  7. 7

    Precision elimination strategy. حسب Yuqi Xiong (12343771)

    منشور في 2025
    "…The algorithm integrates three key strategies: a precise population elimination strategy, which optimizes the population structure by eliminating individuals with low fitness and intelligently generating new ones; a lens imaging-based opposition learning strategy, which expands the exploration of the solution space through reflection and scaling to reduce the risk of local optima; and a boundary control strategy based on the best individual, which effectively constrains the search range to avoid inefficient searches and premature convergence. …"
  8. 8

    Results of low-light image enhancement test. حسب Yuqi Xiong (12343771)

    منشور في 2025
    "…The algorithm integrates three key strategies: a precise population elimination strategy, which optimizes the population structure by eliminating individuals with low fitness and intelligently generating new ones; a lens imaging-based opposition learning strategy, which expands the exploration of the solution space through reflection and scaling to reduce the risk of local optima; and a boundary control strategy based on the best individual, which effectively constrains the search range to avoid inefficient searches and premature convergence. …"
  9. 9

    -value on 23 benchmark functions (dim = 30). حسب Yuqi Xiong (12343771)

    منشور في 2025
    "…The algorithm integrates three key strategies: a precise population elimination strategy, which optimizes the population structure by eliminating individuals with low fitness and intelligently generating new ones; a lens imaging-based opposition learning strategy, which expands the exploration of the solution space through reflection and scaling to reduce the risk of local optima; and a boundary control strategy based on the best individual, which effectively constrains the search range to avoid inefficient searches and premature convergence. …"
  10. 10

    Evaluation metrics obtained by SBOA and MESBOA. حسب Yuqi Xiong (12343771)

    منشور في 2025
    "…The algorithm integrates three key strategies: a precise population elimination strategy, which optimizes the population structure by eliminating individuals with low fitness and intelligently generating new ones; a lens imaging-based opposition learning strategy, which expands the exploration of the solution space through reflection and scaling to reduce the risk of local optima; and a boundary control strategy based on the best individual, which effectively constrains the search range to avoid inefficient searches and premature convergence. …"
  11. 11

    S1 File - حسب Michael Bonert (3751348)

    منشور في 2023
  12. 12

    S2 File - حسب Michael Bonert (3751348)

    منشور في 2023
  13. 13
  14. 14
  15. 15

    Sample image for illustration. حسب Indhumathi S. (19173013)

    منشور في 2024
    "…Furthermore, the matching score for the test image is 0.975. The computation time for CBFD is 2.8 ms, which is at least 6.7% lower than that of other algorithms. …"
  16. 16

    Quadratic polynomial in 2D image plane. حسب Indhumathi S. (19173013)

    منشور في 2024
    "…Furthermore, the matching score for the test image is 0.975. The computation time for CBFD is 2.8 ms, which is at least 6.7% lower than that of other algorithms. …"
  17. 17

    Comparison analysis of computation time. حسب Indhumathi S. (19173013)

    منشور في 2024
    "…Furthermore, the matching score for the test image is 0.975. The computation time for CBFD is 2.8 ms, which is at least 6.7% lower than that of other algorithms. …"
  18. 18

    Process flow diagram of CBFD. حسب Indhumathi S. (19173013)

    منشور في 2024
    "…Furthermore, the matching score for the test image is 0.975. The computation time for CBFD is 2.8 ms, which is at least 6.7% lower than that of other algorithms. …"
  19. 19

    Precision recall curve. حسب Indhumathi S. (19173013)

    منشور في 2024
    "…Furthermore, the matching score for the test image is 0.975. The computation time for CBFD is 2.8 ms, which is at least 6.7% lower than that of other algorithms. …"
  20. 20

    Fortran & C++: design fractal-type optical diffractive element حسب I-Lin Ho (13768960)

    منشور في 2022
    "…</p> <p>(2) calculate diffraction fields for fractal and/or grid-matrix (binary) phase-holograms.</p> <p>(3) optimize the fractal and/or grid-matrix holograms for given target diffraction images, using annealing algorithms. …"