Sentence examples for driving datasets from inspiring English sources

The process of driver fingerprinting consists of first preprocessing the driving datasets, selecting the most relevant features and then developing appropriate classification models using machine learning algorithms.

In order to further evaluate the merits of this approach, more driving datasets must be tested.

This paper addresses the problem of driver identification using real driving datasets consisting of measurements taken from in-vehicle sensors.

This platform relies on datasets of driving and mobility patterns collected by means of navigation systems.

Whole dataset contains driving sessions of six different drivers.

The large number of variables included in this dataset facilitates driving analysis.

This dataset contains driving data for six different drivers and vehicles, D1 through D6, for two different routes, one is 25 km in a road with 3 lanes in each direction and a speed limit of 120 km/h, the other is ~16 km on a secondary road with one lane on each direction and a 90 km/h speed limit.

It might not seem like a lot, but in terms of comparative datasets for highway driving out there, it is.

It is also common to apply economic and environmental factors (even integrating Life Cycle Assessments) to MFA datasets to understand the driving forces and implications of material consumption [5 7].

The UAH-DriveSet is an open dataset obtained by the driving monitoring app "DriveSafe" with the objective of collecting driving data in different environments using smartphones sensors alone.

Next, the combined impacts of climate change and ENSO are simulated by driving MISBA with the ERA-40 dataset re-sampled for active El Niño and La Niña episodes adjusted for climate projections of 2050s.