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INTEL 2021
Learn More Learn More
INTEL® RealSense™
LiDAR CAMERA L515
IEI TECHNOLOGY
MX8 & MX4 AI
ACCELERATOR CARDS
inspect for various types of defects and classify them
accordingly—for example, rework or salvage. When
paired with capable hardware such as one based upon
the 6
th
generation Intel
®
Core
™
processor or Intel's Neural
Compute Stick 2 powered by the Intel Movidius
™
X VPU,
impressive inference speeds can be attained that enable
real-time analytics.
Adapting this Example
Calculating the area of an object on a conveyor belt
can be useful in a variety of environments. Take for an
example the process of sorting fruits and vegetables.
Traditional methods of sorting fruits and vegetables
can lead to bruising. Therefore great care needs to be
employed when handling these items. By adapting this
example to the produce industry, fruits and vegetables
could be inspected and routed based upon their size
(area) and color. Deep learning can also expand on
existing methods by looking at a greater number of
features for grading.
Where to Learn More
You can learn more about this demonstration at Intel's
®
IoT development kit GitHub.
The glue application was developed in the C++ and Go
languages. The distribution includes the Intel
®
optimized
vehicle and pedestrian detection models for OpenVINO
™
.
You can easily experiment with this application using
the Ubuntu 16.04 LTS Linux operating system, the Intel
®
distribution of the OpenVINO
™
toolkit, and the OpenCL
™
runtime package.
You can also jumpstart your development using the AIoT
development kit, which includes Ubuntu, OpenVINO, Intel
®
Media SDK and Intel
®
System Studio 2018 pre-installed
with an Intel
®
Core™ processor. The development kit
includes tutorials to help you get up and running quickly.
You can also use the AAEON UP board based upon the
Intel
®
Apollo Lake
™
platform.
"Calculating the area of an object on a
conveyor belt can be useful in a variety
of environments."