相关实验视频

Updated: Jun 18, 2025

Author Spotlight: Assessment of Visual Acuity in Central Vision Loss Through Motion-Based Peripheral Vision Testing
06:25

Author Spotlight: Assessment of Visual Acuity in Central Vision Loss Through Motion-Based Peripheral Vision Testing

Published on: February 23, 2024

574

通过稀缺特征表示来低拍无监督的视觉异常检测

Fanghui Zhang, Haiyue Zhu, Yigang Cen

    IEEE transactions on neural networks and learning systems
    |July 29, 2024
    PubMed
    概括

    本研究引入了一种用于工业制造的新型稀疏特征表示异常检测 (SFRAD) 框架. 在低射门场景中,SFRAD增强了概括性,在无监督异常检测中超过了现有的方法.

    更多相关视频

    Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications03:31

    Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications

    Published on: December 15, 2023

    512
    Author Spotlight: Efficient Image Recognition Using Directional Gradient Histogram Technique and Support Vector Machines08:27

    Author Spotlight: Efficient Image Recognition Using Directional Gradient Histogram Technique and Support Vector Machines

    Published on: January 5, 2024

    1.0K

    相关概念视频

    What Are Outliers?01:12

    What Are Outliers?

    Outliers are observed data points that are far from the least squares line. They have unusual values and need to be examined carefully. Though an outlier may result from erroneous data, at other times, it may hold valuable information about the population under study and should be included in the data. Hence, it is crucial to examine what causes a data point to be an outlier.
    The z score is used to find outliers or unusual values. It should be noted that any values beyond -2 and +2 are...
    3.7K
    Outliers and Influential Points01:08

    Outliers and Influential Points

    An outlier is an observation of data that does not fit the rest of the data. It is sometimes called an extreme value. When you graph an outlier, it will appear not to fit the pattern of the graph. Some outliers are due to mistakes (for example, writing down 50 instead of 500), while others may indicate that something unusual is happening. Outliers are present far from the least squares line in the vertical direction. They have large "errors," where the "error" or residual is the...
    4.0K
    Unusual Results01:16

    Unusual Results

    Unusual results are those that have a very low chance of occurring. Unusual results can be identified using probabilities and the range rule of thumb. In problems involving probability, unusual results can be observed in 2 instances – an unusually high number of successes or an unusually low number of successes.
    According to the range rule of thumb, any value above or below two standard deviations, 2σ  from the mean, μ  is considered unusual.
    Maximum unusual value =...
    3.2K
    Quantifying and Rejecting Outliers: The Grubbs Test01:02

    Quantifying and Rejecting Outliers: The Grubbs Test

    Sometimes, a data set can have a recorded numerical observation that greatly  deviates from the rest of the data. Assuming that the data is normally distributed, a statistical method called the Grubbs test can be used to determine whether the observation is truly an outlier.  To perform a two-tailed Grubbs test, first, calculate the absolute difference between the outlier and the mean. Then, calculate the ratio between this difference and the standard deviation of the sample. This...
    1.5K