Visiondummy.com Website Review

Usage based insurance solutions where smartphone sensor data is used to an*lyze the driver’s behavior are becoming prevalent these days. However, a major shortcoming of most solutions on the market today, is the fact that trips where the user was a pas*enger, e.g. taxi trips, At Sentiance, we use machine learning to extract intelligence from smartphone sensor data such as accelerometer, gyroscope and location. We’ve been doing this for quite a while now, and are very proud on our state-of-the-art results regarding sensor based activity detection, map matching, driving behavior, venue mapping and.. Continue reading » works, and how it can be used as a dimensionality reduction technique for clas*ification problems. At the end of this article, Matlab source code is provided for demonstration purposes. In an earlier article, we discussed the so called.. Continue reading » the covariance matrix, by exploring the relation between linear transformations and the resulting data covariance. Most textbooks explain the shape of data based on the concept of covariance matrices. Instead, we take a backwards approach and explain the.. Continue Dimensionality’, and explain why it is important when designing a clas*ifier. In the following sections I will provide an intuitive explanation of this concept, illustrated by a clear example of overfitting due to the curse of dimensionality... Continue reading » confidence ellipse, for 2D normally distributed data. The error ellipse represents an iso-contour of the Gaussian distribution, and allows you to visualize a 2D confidence interval. The following figure shows a 95% confidence ellipse for.. Continue reading » In this article, we will derive the well known formulas for calculating the mean and the variance of normally distributed data, in order to answer the question in the article’s title. However, for readers who are not interested in the ‘why’ of this question but computer vision and machine learning in general. Well known examples are PCA (Principal Component An*lysis) for dimensionality reduction or