بدائل البحث:
complex optimization » convex optimization (توسيع البحث), wolf optimization (توسيع البحث), codon optimization (توسيع البحث)
whale optimization » swarm optimization (توسيع البحث)
binary based » library based (توسيع البحث), linac based (توسيع البحث), binary mask (توسيع البحث)
based whale » based whole (توسيع البحث), baleen whale (توسيع البحث), based halide (توسيع البحث)
final layer » single layer (توسيع البحث)
complex optimization » convex optimization (توسيع البحث), wolf optimization (توسيع البحث), codon optimization (توسيع البحث)
whale optimization » swarm optimization (توسيع البحث)
binary based » library based (توسيع البحث), linac based (توسيع البحث), binary mask (توسيع البحث)
based whale » based whole (توسيع البحث), baleen whale (توسيع البحث), based halide (توسيع البحث)
final layer » single layer (توسيع البحث)
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21
The workflow of EGA-BPNN.
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. …"
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22
S1 Data -
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. …"
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23
Fusion effectiveness of 6 groups of images.
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. …"
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24
Overall flowchart of Multi-agent fusion model.
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. …"
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25
Fusion performance of 3 groups fusion structures.
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. …"
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26
Fusion rule set.
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. …"
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27
Comparison with existing SOTA techniques.
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. …"
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28
Proposed inverted residual parallel block.
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. …"
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29
Inverted residual bottleneck block.
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. …"
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30
Proposed architecture testing phase.
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. …"
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31
Sample classes from the HMDB51 dataset.
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. …"
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32
Sample classes from UCF101 dataset [40].
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. …"
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33
Self-attention module for the features learning.
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. …"
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34
Residual behavior.
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. …"
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35
Dongfanghong tractor.
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. …"
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36
Experimental equipment parameters.
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. …"
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37
Coordinate Conversion Process.
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. …"
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38
Data for parameters.
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. …"
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39
Semantic Label Addition Process.
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. …"
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40
Minimum obstacle avoidance distance test results.
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. …"