The NXP eIQ® Auto deep learning (DL) toolkit enables developers to introduce DL algorithms into their applications and to continue satisfying automotive standards. The eIQ Auto software and accompanying tools within the toolkit help developers move quickly and easily from a development environment to full implementation of AI applications in automotive-grade embedded processors.
Lidar assists in classifying objects within the scene, such as cars, pedestrians, and cyclists in visually tough environments such as rain, fog, and low light conditions.
Object Detection, classification, and tracking are essential for vision-based New Car Assessment Program (NCAP) automated driving functions.
Front View Camera systems in advanced driver assistance systems can analyze the video content for lane departure warning (LDW), automatic lane keeping assist (LKA), high/low beam headlight control, and traffic sign recognition (TSR).
Learn more about Front View Camera
Multicamera Surround View captures and displays onscreen the area surrounding the car from a virtual 3D view, providing a 360° view around the car.
Learn more about Surround View
Sense park assist systems provides perspective that is dynamically moves depending upon the trajectory of the car.
Driving monitoring systems (DMS) can provide alerts to the driver and initiate an intervention to manage the control of the vehicle, helping reduce accidents. NXP offers dedicated silicon solutions for both DMS and occupant monitoring systems in partnership with Momenta.
Watch a DMS with S32V234 demo video
Innovation for the future with deep learning algorithms made easier. NXP eIQ Auto toolkit will assist your engineers in developing automotive applications, such as driver monitoring systems and object detection, utilizing deep learning algorithms.
Start exploring the capability of porting your deep learning algorithms based on S32V234. Bring your application to life!
Learn more about the processing efficiency, accelerated development and deployment workflows for AI automotive applications as well as how eIQ Auto Deep Learning toolkit assists your application development.
As society talks more about artificial intelligence and the role it will play in our future, a key question that NXP is looking at is how to make AI and ML safe in terms of our development processes?
Learn about the eIQ Machine Learning Software and eIQ Auto and explore inference engine options for S32G, i.MX, i.MX RT and S32V processors.
Learn to implement and configure the NXP eIQ® Auto deep learning toolkit to optimize and implement DL without the need for customized hardware expertise.
Explore ways of dealing with these challenges and view an example of an optimized workflow for deploying deep learning in automotive production vehicles using the NXP eIQ® auto deep learning toolkit.
eIQ Auto Deep Learning toolkit is a part of the eIQ software environment for machine and deep learning, with inference engines for developing embedded machine learning applications.
