Computer Vision Model Zoo for Ambarella chipsets


CVEDIA creates edge computer vision applications for Ambarella chipsets using only synthetic data – bringing you to market faster, cheaper, and without any more data collection.




Custom Ambarella software

CVEDIA creates edge algorithm solutions for Ambarella chipsets including Cortex A9, Cortex A53, and Cortex A76, with a model zoo containing 24+ off-the-shelf algorithms.

Depending on your requirements, our solutions team can target your model to work better for accuracy or performance, and then optimize it to function at full capacity using device-specific computing capabilities. This provides our clients with a head start on their competition, especially considering the lag time involved in data collection.

By skillfully utilizing synthetic data, we can provide edge algorithms for Ambarella in 2-4 weeks, rather than months to years.

CVEDIA | Custom Ambarella software



CVEDIA | Ambarella product line and resources


Ambarella product line and resources

CVEDIA currently deploys to the following Ambarella chipsets:

  • CV22.

  • CV25.

  • S3L.

  • S5L.

With over 24 off-the-shelf algorithms and endless customization capabilities, including unique classes, classification, and device-specific computing capabilities.



The acceleration of artificial intelligence in automotive.



Ambarella introduces CV5 high performance AI vision processor for single 8K and multi-imager AI cameras.



Delivering smart cameras to the masses.


CVEDIA | Amazon Web Services
CVEDIA | Resolve
CVEDIA | Qualcomm
CVEDIA | NVIDIA
CVEDIA | Teledyne FLIR


EDGE DEPLOYMENT

CVEDIA's synthetic algorithms are optimized to run locally on low power devices, and designed to integrate seamlessly with hardware devices.


ADVANCED PERFORMANCE

By employing proprietary synthetic data technology, CVEDIA AI is stronger, more resilient, and better at generalizing.


RUNS ANYWHERE

Our software is not vendor locked, this means that it has been specifically designed to run across all edge devices.