FLIR Insights

Insights March 2017

Insights Newsletter
Problem Solving Lesson #4

Lesson #4: Use FLIR cameras, open source libraries, and Nvidia hardware to access the benefits of deep learning


Use FLIR cameras, open-source libraries, and NVidia hardware to leverage deep learning

With open-source libraries like Google's TensorFlow providing access to deep learning methods, machine vision developers can automate dynamic decision-making systems quickly and easily. In this lesson, we provide a brief overview of deep learning and explain how FLIR and NVidia use it to train automated decision-making systems and deploy them on powerful, affordable, embedded platforms.

Bullet  How can I access the benefits of deep learning?

FIAT reduces injury with thermal testing during production

An Autonomous Vehicle Driven Solely by Cameras Without Lasers


FIAT uses thermal testing during production to reduce car accident injuries

A car needs a rigid internal structure with flexible exterior components to prevent pedestrian injuries in a traffic accident. To create cars with these properties, FIAT bonds materials with adhesives. Material adhesion is confirmed while production is in operation using Italian equipment maker Inprotec's process, featuring FLIR's thermal A615 camera.

Bullet  Download case study
Bullet  Learn more about FLIR's A series cameras
Bullet  Send an inquiry to FLIR's automation team

An autonomous vehicle driven solely by cameras

Oxford is conducting a research project whose goal is to create an autonomous car that uses cameras as its sole means of data acquisition. Vehicle orientation is determined by matching experience data previously captured by FLIR's Bumblebee® XB3 stereo camera with 'live' images captured by three Grasshopper®2 cameras.

Bullet  Read more

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Streaming Cameras on Embedded Systems

Streaming Cameras on Embedded Systems

Getting Started with FlyCapture 2 and ARM

Getting Started with FlyCapture 2 and ARM

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