Search alternatives:
significantly improved » significantly increased (Expand Search)
significantly linear » significant linear (Expand Search), significantly lower (Expand Search), significantly longer (Expand Search)
improved decrease » improved urease (Expand Search), marked decrease (Expand Search)
linear decrease » linear increase (Expand Search)
significantly improved » significantly increased (Expand Search)
significantly linear » significant linear (Expand Search), significantly lower (Expand Search), significantly longer (Expand Search)
improved decrease » improved urease (Expand Search), marked decrease (Expand Search)
linear decrease » linear increase (Expand Search)
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Improved model distillation structure.
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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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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Recruitment flow diagram of the current study.
Published 2025“…</p><p>Conclusions</p><p>Clinicians should assess and address patients’ recovery expectations early in the care process, as these may significantly influence long-term HRQoL outcomes. Incorporating strategies to support realistic yet positive expectations, such as cognitive-behavioral therapy, structured patient education, and goal-setting programs, may improve recovery experiences. …”
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