Self-driving cars or also known as autonomous vehicles are complex machines that need to be trained by Machine Learning algorithms. These algorithms are powered by training data which then helps the self-driving cars to process visual data and identify obstacles and understand the surroundings while driving. To know more about the blog, click here - http://datalabeler.com/training-data-for-self-driving-cars/ Data Labeler offers a range of data annotation services like bounding box and polygon annotations that help to power the self-driving cars or autonomous vehicles. Click the link to know more - http://datalabeler.com/

2. Why Training Data is Required for
Autonomous Cars?
Self-driving cars need to understand their environment which enables
safety driving. Machine Learning algorithms enables self-driving cars to
process visual information similar to human drive and identifies
obstacles such as tree or a pedestrian.These ML algorithms have to be
trained first labeled data which powers the autonomous vehicles.

3. Pre-requisites for Training Data
Clarity –
Guidelines on
what objects
qualify for
labeling
RightToolsets
– Different
types of
annotations
require
different
toolsets
Economy –
Outsourcing
data labeling
needs to
third-parties
is
economically
more viable
option for
companies.

4. Want to know more about training data for self-driving cars?
Looking for quality image labeling services?
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