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相关概念视频

Improving Translational Accuracy02:07

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Base complementarity between the three base pairs of mRNA codon and the tRNA anticodon is not a failsafe mechanism. Inaccuracies can range from a single mismatch to no correct base pairing at all. The free energy difference between the correct and nearly correct base pairs can be as small as 3 kcal/ mol. With complementarity being the only proofreading step, the estimated error frequency would be one wrong amino acid in every 100 amino acids incorporated. However, error frequencies observed in...
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The limit of detection (LOD) is the smallest amount of analyte that can be distinguished from the background noise. The LOD value corresponds to the concentration at which the analyte signal is three times larger than the standard deviation of the blank signal. Below this value, the analyte signal cannot be differentiated from the background noise. It is calculated by dividing the calibration slope by 3 times the standard deviation of the blank signals.
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目标感知变压器跟踪与硬封闭实例生成

Dingkun Xiao1, Zhenzhong Wei1, Guangjun Zhang1

  • 1Key Laboratory of Precision Opto-Mechatronics Technology, Ministry of Education, School of Instrumentation and Opto-Electronics Engineering, Beihang University, Beijing, China.

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概括
此摘要是机器生成的。

这项研究介绍了TATT,一种新的变压器跟踪方法,可以改善隐蔽场景中的视觉跟踪. 在遮蔽过程中,TATT通过有效处理不完整的外观信息来增强目标识别.

关键词:
深度学习是一种深度学习.一个实例的生成实例的生成.封闭性封闭是什么?有目标意识的目标意识.变压器的变压器是一个变压器.视觉跟踪 视觉跟踪 视觉跟踪

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科学领域:

  • 计算机视觉 计算机视觉
  • 深度学习 (Deep Learning) 是一种深度学习.
  • 对象跟踪是指对象的跟踪.

背景情况:

  • 变压器架构在视觉跟踪方面越来越占主导地位,超过了姆网络.
  • 目前的基于变压器的追踪器因难以识别不完整的目标信息而扎于被遮蔽的场景.

研究的目的:

  • 提出一种新的变压器跟踪方法,TATT,旨在提高在视觉跟踪场景中的性能.
  • 解决现有追踪器在识别具有不完整外观数据的目标方面的局限性.

主要方法:

  • 开发了一个具有编码器-解码器结构的目标感知变压器网络,用于功能交互.
  • 集成了一个硬封闭实例生成模块,使用图像相似性创建现实的封闭场景.
  • 目标感知变压器直接预测追踪结果的目标边界.

主要成果:

  • 在五个基准 (LaSOT,TrackingNet,Got10k,OTB100,UAV123) 上,TATT表现出令人期待的表现.
  • 在LaSOT数据集上获得了65.5% (部分封闭) 和61.2% (完全封闭) 的最新AUC得分.
  • 追踪器在GPU上以每秒大约41的速度运行.

结论:

  • 在具有挑战性的封闭环境中,TATT有效地提高了视觉跟踪准确度.
  • 提出的方法成功处理不完整的目标外观信息,优于现有的方法.
  • 塔特为现实世界的视觉跟踪应用提供了强大而高效的解决方案.