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significantly improved » significantly increased (Expand Search)
significantly longer » significantly lower (Expand Search), significantly larger (Expand Search), significantly higher (Expand Search)
improved decrease » improved urease (Expand Search), marked decrease (Expand Search)
longer decrease » larger decrease (Expand Search), linear decrease (Expand Search), largest decrease (Expand Search)
significantly improved » significantly increased (Expand Search)
significantly longer » significantly lower (Expand Search), significantly larger (Expand Search), significantly higher (Expand Search)
improved decrease » improved urease (Expand Search), marked decrease (Expand Search)
longer decrease » larger decrease (Expand Search), linear decrease (Expand Search), largest decrease (Expand Search)
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Conditional autonomous driving scenario complexity factor perceptual weights.
Published 2025Subjects: -
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Three display types of autonomous driving information on the HUD in the Chinese vehicle market.
Published 2025Subjects: -
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Comparison experiment of accuracy improvement.
Published 2025“…Secondly, a lightweight convolutional module is introduced to replace the standard convolutions in the Efficient Long-range Aggregation Network (ELAN-A) module, and the channel pruning techniques are applied to further decrease the model’s complexity. Finally, the experiment significantly enhanced the efficiency of feature extraction and the detection accuracy of the model algorithm through the integration of the Dynamic Head (DyHead) module, the Content-Aware Re-Assembly of Features (CARAFE) module, and the incorporation of knowledge distillation techniques. …”
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Comparison experiment of accuracy improvement.
Published 2025“…Secondly, a lightweight convolutional module is introduced to replace the standard convolutions in the Efficient Long-range Aggregation Network (ELAN-A) module, and the channel pruning techniques are applied to further decrease the model’s complexity. Finally, the experiment significantly enhanced the efficiency of feature extraction and the detection accuracy of the model algorithm through the integration of the Dynamic Head (DyHead) module, the Content-Aware Re-Assembly of Features (CARAFE) module, and the incorporation of knowledge distillation techniques. …”
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Improvement of CBS to CBR process.
Published 2025“…Furthermore, Parameters and GFLOPs were reduced by 10.0% and 23.2%, respectively, indicating a significant enhancement in detection accuracy along with a substantial decrease in both parameters and computational costs. …”
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