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相关概念视频

The Spindle Assembly Checkpoint02:19

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The spindle assembly checkpoint is a molecular surveillance mechanism ensuring the fidelity of chromosome segregation during anaphase. The checkpoint monitors the completion of all the prerequisite steps before chromosome segregation to determine whether the segregation process should proceed or be delayed.
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Electronic Distance Measuring Instruments (EDMs) are essential tools in modern surveying, offering precise distance measurements by emitting electromagnetic signals and calculating the time required for these signals to travel to a target and return. Two primary types of signals are used in EDMs — light waves and microwaves — each suited to specific environmental and distance requirements. Light-wave-based EDMs utilize either infrared or laser light, providing high accuracy over short...
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Spindle assembly occurs through three, often coexisting, pathways – the centrosome-mediated pathway, the chromatin-mediated pathway, and the microtubule-mediated pathway – collectively contributing to form a robust spindle apparatus.
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Distribution reliability in electrical power systems is critical for ensuring an uninterrupted power supply to consumers at minimal cost. According to IEEE Standard Terms, reliability is the probability that a device will function without failure over a specified time period or amount of usage. For electric power distribution, this translates to maintaining continuous power supply and addressing customer concerns over power outages. Several indices, as defined by IEEE Standard 1366-2012, are...
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The fast decoupled power flow method addresses contingencies in power system operations, such as generator outages or transmission line failures. This method provides quick power flow solutions, essential for real-time system adjustments. Fast decoupled power flow algorithms simplify the Jacobian matrix by neglecting certain elements, leading to two sets of decoupled equations:
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In mechanical engineering, one-degree-of-freedom systems form the basis of a wide range of electrical and mechanical components. Using these models, engineers can predict the behavior of various parts in a larger system, which gives them insight into how different forces interact with each other.
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Updated: Jul 19, 2025

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解边缘指导网络用于自动结账.

Rongbiao You1, Fuxiong He2, Weiming Lin1,3

  • 1School of Opto-Electronic and Communication Engineering, Xiamen University of Technology, Xiamen 361024, P. R. China.

International journal of neural systems
|August 11, 2023
PubMed
概括
此摘要是机器生成的。

本研究介绍了DEGNet,以弥合自动结账 (ACO) 系统中的域差距. 通过使用边缘信息整合真实和合成数据,DEGNet 改进了从结账图像生成购物清单.

关键词:
自动结账 自动结账域名适应 域名适应边缘指导 边缘指导对象检测检测对象检测对象检测

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科学领域:

  • 计算机视觉 计算机视觉
  • 机器学习 机器学习
  • 人工智能的人工智能

背景情况:

  • 自动结账 (ACO) 系统面临挑战,因为单一产品培训数据和多个产品现实结账图像之间的域差距很大.
  • 现有的方法很难将合成图像推广到现实的结账场景,从而限制了ACO的性能.

研究的目的:

  • 提出一个新的脱边缘指导网络 (DEGNet),以解决自动结账中的域差距.
  • 为了提高从结账图片生成完整购物清单的准确性.

主要方法:

  • 实施了监督域调整方法,集成合成和检查图像.
  • 开发了一个边缘嵌入模块来引入边缘信息和一个解的特征提取器,用于联合图像和边缘数据的利用.
  • 提出了一项划分与征服策略 (PDS) 提案,以增加高质量的培训样本.

主要成果:

  • 在零售产品结账 (RPC) 数据集上,DEGNet 实现了最先进的性能.
  • 使用Faster R-CNN实现了93.47%的结账精度 (cAcc),使用Cascade R-CNN实现了95.25%的结账精度.

结论:

  • 拟议的DEGNet有效地弥合了自动结账系统中的域差距.
  • 边缘信息的整合和PDS策略显著提高了ACO在现实世界结账图像上的性能.