يعرض 21 - 40 نتائج من 44 نتيجة بحث عن '(( binary based whale optimization algorithm ) OR ( final layer complex optimization algorithm ))', وقت الاستعلام: 0.36s تنقيح النتائج
  1. 21

    The workflow of EGA-BPNN. حسب Xiying Wang (4859998)

    منشور في 2025
    "…To address these problems, a genetic algorithm (GA) is adopted for optimizing the BPNN, and the EGA-BPNN model is used to predict irrigation flow in agricultural fields. …"
  2. 22

    S1 Data - حسب Xiying Wang (4859998)

    منشور في 2025
    "…To address these problems, a genetic algorithm (GA) is adopted for optimizing the BPNN, and the EGA-BPNN model is used to predict irrigation flow in agricultural fields. …"
  3. 23

    Fusion effectiveness of 6 groups of images. حسب Yandong Liu (11893664)

    منشور في 2025
    "…Finally, in the context of a complex fusion process, the multi-agent fusion model performs the fusion task through the collaborative interaction of multiple fusion agents. …"
  4. 24

    Overall flowchart of Multi-agent fusion model. حسب Yandong Liu (11893664)

    منشور في 2025
    "…Finally, in the context of a complex fusion process, the multi-agent fusion model performs the fusion task through the collaborative interaction of multiple fusion agents. …"
  5. 25

    Fusion performance of 3 groups fusion structures. حسب Yandong Liu (11893664)

    منشور في 2025
    "…Finally, in the context of a complex fusion process, the multi-agent fusion model performs the fusion task through the collaborative interaction of multiple fusion agents. …"
  6. 26

    Fusion rule set. حسب Yandong Liu (11893664)

    منشور في 2025
    "…Finally, in the context of a complex fusion process, the multi-agent fusion model performs the fusion task through the collaborative interaction of multiple fusion agents. …"
  7. 27

    Comparison with existing SOTA techniques. حسب Yasir Khan Jadoon (21433231)

    منشور في 2025
    "…The learned weights of the first module are passed to self-attention, extract the most essential features, and can easily discriminate complex human actions. The proposed architecture is trained on the selected datasets, whereas the hyperparameters are chosen using the particle swarm optimization (PSO) algorithm. …"
  8. 28

    Proposed inverted residual parallel block. حسب Yasir Khan Jadoon (21433231)

    منشور في 2025
    "…The learned weights of the first module are passed to self-attention, extract the most essential features, and can easily discriminate complex human actions. The proposed architecture is trained on the selected datasets, whereas the hyperparameters are chosen using the particle swarm optimization (PSO) algorithm. …"
  9. 29

    Inverted residual bottleneck block. حسب Yasir Khan Jadoon (21433231)

    منشور في 2025
    "…The learned weights of the first module are passed to self-attention, extract the most essential features, and can easily discriminate complex human actions. The proposed architecture is trained on the selected datasets, whereas the hyperparameters are chosen using the particle swarm optimization (PSO) algorithm. …"
  10. 30

    Proposed architecture testing phase. حسب Yasir Khan Jadoon (21433231)

    منشور في 2025
    "…The learned weights of the first module are passed to self-attention, extract the most essential features, and can easily discriminate complex human actions. The proposed architecture is trained on the selected datasets, whereas the hyperparameters are chosen using the particle swarm optimization (PSO) algorithm. …"
  11. 31

    Sample classes from the HMDB51 dataset. حسب Yasir Khan Jadoon (21433231)

    منشور في 2025
    "…The learned weights of the first module are passed to self-attention, extract the most essential features, and can easily discriminate complex human actions. The proposed architecture is trained on the selected datasets, whereas the hyperparameters are chosen using the particle swarm optimization (PSO) algorithm. …"
  12. 32

    Sample classes from UCF101 dataset [40]. حسب Yasir Khan Jadoon (21433231)

    منشور في 2025
    "…The learned weights of the first module are passed to self-attention, extract the most essential features, and can easily discriminate complex human actions. The proposed architecture is trained on the selected datasets, whereas the hyperparameters are chosen using the particle swarm optimization (PSO) algorithm. …"
  13. 33

    Self-attention module for the features learning. حسب Yasir Khan Jadoon (21433231)

    منشور في 2025
    "…The learned weights of the first module are passed to self-attention, extract the most essential features, and can easily discriminate complex human actions. The proposed architecture is trained on the selected datasets, whereas the hyperparameters are chosen using the particle swarm optimization (PSO) algorithm. …"
  14. 34

    Residual behavior. حسب Yasir Khan Jadoon (21433231)

    منشور في 2025
    "…The learned weights of the first module are passed to self-attention, extract the most essential features, and can easily discriminate complex human actions. The proposed architecture is trained on the selected datasets, whereas the hyperparameters are chosen using the particle swarm optimization (PSO) algorithm. …"
  15. 35

    Dongfanghong tractor. حسب Ningjie Chang (21402721)

    منشور في 2025
    "…<div><p>The accuracy and consistency of obstacle avoidance map construction are poor in complex and changeable dynamic environment. In order to improve the driving safety of mountain tractors in complex mountain environment, an autonomous obstacle avoidance method for mountain tractors based on semantic neural network and laser SLAM was studied. …"
  16. 36

    Experimental equipment parameters. حسب Ningjie Chang (21402721)

    منشور في 2025
    "…<div><p>The accuracy and consistency of obstacle avoidance map construction are poor in complex and changeable dynamic environment. In order to improve the driving safety of mountain tractors in complex mountain environment, an autonomous obstacle avoidance method for mountain tractors based on semantic neural network and laser SLAM was studied. …"
  17. 37

    Coordinate Conversion Process. حسب Ningjie Chang (21402721)

    منشور في 2025
    "…<div><p>The accuracy and consistency of obstacle avoidance map construction are poor in complex and changeable dynamic environment. In order to improve the driving safety of mountain tractors in complex mountain environment, an autonomous obstacle avoidance method for mountain tractors based on semantic neural network and laser SLAM was studied. …"
  18. 38

    Data for parameters. حسب Ningjie Chang (21402721)

    منشور في 2025
    "…<div><p>The accuracy and consistency of obstacle avoidance map construction are poor in complex and changeable dynamic environment. In order to improve the driving safety of mountain tractors in complex mountain environment, an autonomous obstacle avoidance method for mountain tractors based on semantic neural network and laser SLAM was studied. …"
  19. 39

    Semantic Label Addition Process. حسب Ningjie Chang (21402721)

    منشور في 2025
    "…<div><p>The accuracy and consistency of obstacle avoidance map construction are poor in complex and changeable dynamic environment. In order to improve the driving safety of mountain tractors in complex mountain environment, an autonomous obstacle avoidance method for mountain tractors based on semantic neural network and laser SLAM was studied. …"
  20. 40

    Minimum obstacle avoidance distance test results. حسب Ningjie Chang (21402721)

    منشور في 2025
    "…<div><p>The accuracy and consistency of obstacle avoidance map construction are poor in complex and changeable dynamic environment. In order to improve the driving safety of mountain tractors in complex mountain environment, an autonomous obstacle avoidance method for mountain tractors based on semantic neural network and laser SLAM was studied. …"