Jove
Visualize
联系我们
JoVE
x logofacebook logolinkedin logoyoutube logo
关于 JoVE
概览领导团队博客JoVE 帮助中心
作者
出版流程编辑委员会范围与政策同行评审常见问题投稿
图书馆员
用户评价订阅访问资源图书馆顾问委员会常见问题
研究
JoVE JournalMethods CollectionsJoVE Encyclopedia of Experiments存档
教育
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab Manual教师资源中心教师网站
使用条款与条件
隐私政策
政策

相关概念视频

Residuals and Least-Squares Property01:11

Residuals and Least-Squares Property

7.4K
The vertical distance between the actual value of y and the estimated value of y. In other words, it measures the vertical distance between the actual data point and the predicted point on the line
If the observed data point lies above the line, the residual is positive, and the line underestimates the actual data value for y. If the observed data point lies below the line, the residual is negative, and the line overestimates the actual data value for y.
The process of fitting the best-fit...
7.4K
Distribution Reliability and Automation01:25

Distribution Reliability and Automation

108
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...
108
Clearance Models: Noncompartmental Models01:17

Clearance Models: Noncompartmental Models

62
Clearance is a pharmacokinetic parameter traditionally defined by compartment models, signifying the rate at which a drug is expelled from the body. However, a noncompartmental model offers an alternative method for assessing clearance, primarily employing empirical data obtained after administering a single drug dose.
The noncompartmental approach capitalizes on extensive sampling data, correlating the volume of distribution to systemic exposure and the administered dosage. This method enables...
62
Reducing Line Loss01:18

Reducing Line Loss

154
In a three-phase circuit, line loss is an indicator of energy dissipated as heat due to the resistance of transmission lines. To address this, incorporating transformers into the system—a step-up transformer at the source and a step-down transformer at the load—is a strategic solution. Two three-phase transformers are introduced to improve this.
With a step-up transformer at the source, the voltage is increased, thereby reducing the current in the transmission lines since power loss...
154
Clearance Models: Compartment Models01:25

Clearance Models: Compartment Models

82
Clearance measures drug elimination from the central compartment, including plasma and highly perfused organs like kidneys and liver. Its calculation varies depending on pharmacokinetic models and administration routes. The one-compartment model, for instance, portrays the pharmacokinetics of polar drugs such as aminoglycoside antibiotics administered intravenously and readily excreted in urine. In this case, clearance is influenced by the terminal rate constant (λz) and the total volume...
82
Model-Independent Approaches for Pharmacokinetic Data: Noncompartmental Analysis00:59

Model-Independent Approaches for Pharmacokinetic Data: Noncompartmental Analysis

66
Noncompartmental analyses offer an alternative method for describing drug pharmacokinetics without relying on a specific compartmental model. In this approach, the drug's pharmacokinetics are assumed to be linear, with the terminal phase log-linear. This assumption allows for simplified analysis and interpretation of the drug's behavior in the body.
One important characteristic of noncompartmental analyses is that drug exposure increases proportionally with increasing doses. This...
66

您也可能阅读

相关文章

通过共同作者、期刊和引用图与本文相关的文章。

排序
Same author

Current Status and Emerging Trends in Global Research on Liposome Therapy for Hepatocellular Carcinoma: A Bibliometric Analysis.

Journal of hepatocellular carcinoma·2026
Same author

A phase I, randomized, dose-escalation clinical trial of the anti-IgE humanized monoclonal antibody LP-003 in healthy subjects.

Combinatorial chemistry & high throughput screening·2026
Same author

Integrative Database-Driven In Silico and In Vitro Study of Anemarrhena asphodeloides Bunge Highlighting Hippeastrine as a Regulator of the HSP90/PI3K/Akt/mTOR Axis in Oral Squamous Cell Carcinoma.

Advanced biology·2026
Same author

Wake modeling for offshore floating wind farms incorporating time-lag effects in yaw and pitch states.

Scientific reports·2026
Same author

CFD Investigation of the Effect of Condensation Chamber Geometry on Nanoparticle Transport in Magnetron Sputtering.

Nanomaterials (Basel, Switzerland)·2026
Same author

Gonyautoxins induce cytotoxicity in human intestinal Caco-2 cells: Oxidative stress, apoptosis, and transcriptional responses.

Marine pollution bulletin·2026

相关实验视频

Updated: Jul 8, 2025

Using a Virtual Store As a Research Tool to Investigate Consumer In-store Behavior
09:17

Using a Virtual Store As a Research Tool to Investigate Consumer In-store Behavior

Published on: July 24, 2017

11.4K

智能零售SKU结账使用改进的剩余网络.

Chunchieh Wang1, Chengwei Huang2, Xiaoming Zhu2

  • 1School of Instrument Science and Engineering, Southeast University, Nanjing, 210000, China.

Scientific reports
|December 18, 2023
PubMed
概括

本研究引入了无人店的先进零售产品检测算法,提高了库存单元 (SKU) 识别准确性和运营效率. 这种新的方法可以在杂乱的环境中增强物品检测,加快客户结账流程.

更多相关视频

Spotlighting Customers' Visual Attention at the Stock, Shelf and Store Levels with the 3S Model
06:30

Spotlighting Customers' Visual Attention at the Stock, Shelf and Store Levels with the 3S Model

Published on: May 24, 2019

5.3K
Author Spotlight: Assessing Brain Activity in Robotic-Assisted Lower Limb Rehabilitation Using fNIRS
05:25

Author Spotlight: Assessing Brain Activity in Robotic-Assisted Lower Limb Rehabilitation Using fNIRS

Published on: June 7, 2024

1.2K

相关实验视频

Last Updated: Jul 8, 2025

Using a Virtual Store As a Research Tool to Investigate Consumer In-store Behavior
09:17

Using a Virtual Store As a Research Tool to Investigate Consumer In-store Behavior

Published on: July 24, 2017

11.4K
Spotlighting Customers' Visual Attention at the Stock, Shelf and Store Levels with the 3S Model
06:30

Spotlighting Customers' Visual Attention at the Stock, Shelf and Store Levels with the 3S Model

Published on: May 24, 2019

5.3K
Author Spotlight: Assessing Brain Activity in Robotic-Assisted Lower Limb Rehabilitation Using fNIRS
05:25

Author Spotlight: Assessing Brain Activity in Robotic-Assisted Lower Limb Rehabilitation Using fNIRS

Published on: June 7, 2024

1.2K

科学领域:

  • 计算机科学 计算机科学
  • 人工智能的人工智能
  • 机器学习 机器学习

背景情况:

  • 无人商店需要高效的操作系统.
  • 自动化库存单位 (SKU) 的识别对于加速客户结账至关重要.
  • 现有的通用检测算法在零售环境中面临挑战,例如密集的项目安排,规模变化和产品相似性.

研究的目的:

  • 为无人商店开发一个改进的零售产品检测算法.
  • 提高库存单位 (SKU) 识别的准确性和效率.
  • 为了应对检测密集排列,不同规模和相似外观的零售产品的特殊挑战.

主要方法:

  • 提出了一种新的边界回归神经网络架构,用于在密集的布局中增强边界框检测,减少计算成本和参数大小.
  • 引入了一种新的损失函数用于层次检测,以解决正负样本中的不平衡问题.
  • 增强的非最大抑制 (NMS) 与加权的非最大抑制 (WNMS),将NMS排名得分与候选框准确性联系起来.

主要成果:

  • 与SKU-110K和RPC数据集上的现有方法相比,拟议的算法显示出更好的可靠性和效率.
  • 新的边界回归网络有效地处理了密集项目的安排.
  • 层次损失函数和WNMS有助于更准确的产品检测.

结论:

  • 开发的零售产品检测算法显著提高了无人店SKU识别.
  • 提出的方法有效地减轻了与密集的项目安排,规模变化和产品相似性相关的挑战.
  • 这一进步有助于提高运营效率和改善零售环境中的客户体验.