If you are using computer vision techniques like image classification and object detection, here are some resources from Arm and partners that can help. Advancements in deep learning, neural networks and embedded compute capabilities enables machine vision on low-power Cortex-M processors, as well as even more efficiency for Cortex-A based devices. Go to section:

Computer vision on Cortex-M | Computer vision on Cortex-A | Get Support

Computer vision on Cortex-M

Image recognition with TensorFlow

Learn how to use Tensorflow Lite for Microcontrollers to run a neural network to recognize people in images.

View guide

Image recognition on the Cortex-M1 processor

Create a low-cost image solution using a Xilinx Spartan S7 FPGA, the Xilinx Vivado Design Suite and Keil MDK.

View guide

Person detection with CMSIS-NN and TensorFlow Lite for Microcontrollers

Detect a person on the Arduino Nano BLE Sense with CMSIS-NN optimizations in Tensorflow Lite for Microcontrollers.

Watch video

Adding sight to your sensors

Use ML to build a system that can recognize objects in a house using the OpenMV Cam H7 Plus and Edge Impulse.

View guide

MNIST handwriting recognition

Build a MNIST handwriting recognition app using TensorFlow Lite for Microcontrollers on a Cortex M7-based processor.

View guide

Smile detection with OpenMV IDE and Edge Impulse

Train powerful Convolutional Neural Networks in the cloud for any application, and have them run on the OpenMV Cam in just 15 minutes.

Watch video

Add intelligent vision

Understand the concepts of adding intelligent vision to your next embedded device.

Download paper

Computer vision on Cortex-A

Get started

Train your Raspberry Pi to detect what gesture you are performing, through transfer learning.

Watch video
View guide

More robust models

Build and train a more robust model, to have your Raspberry Pi detect multiple gestures.

Watch video
View guide

Image analysis on Raspberry Pi

Build an Arm NN-based application for an IoT device that performs automatic trash sorting using image analysis.

View guide

ML solutions on embedded devices

Use the Au-Zone DeepView ML toolkit for on-target runtime performance on vision applications.

Watch webinar

Profile AlexNet on Raspberry Pi and HiKey 960

Use Streamline to profile the AlexNet example application from the Arm Compute Library for Raspberry Pi and the HiKey 960 board.

View guide

Run AlexNet on Raspberry Pi

Develop a Convolutional Neural Network (CNN) called AlexNet using the Arm Compute Library and a Raspberry Pi.

View guide

Accelerate ML using Compute Library on HiKey 960

Run ML applications on a high development platform using the HiKey 960, a mobile development platform built on Arm Cortex processors and Mali GPUs.

Watch webinar

Get Support


Community Blogs

Community Forums

Suggested answer Is it possible to turn my phone's 64-bit armv8-a (32-bit mode) to 64 bit mode 0 votes 135 views 1 replies Latest 10 hours ago by Raheem Answer this
Not answered M0+ Thumb - C flag 0 votes 91 views 0 replies Started 18 hours ago by Sean Dunlevy Answer this
Suggested answer CPSR status back to C variable
  • Arm7
  • Compilers
  • C
0 votes 2531 views 3 replies Latest yesterday by Frost13 Answer this
Suggested answer Is pre-compiled ARM9 libs able to run on an ARM11 chip
  • Arm9
  • Arm11
0 votes 1826 views 4 replies Latest 2 days ago by Andy Neil Answer this
Suggested answer Is it possible to turn my phone's 64-bit armv8-a (32-bit mode) to 64 bit mode Latest 10 hours ago by Raheem 1 replies 135 views
Not answered M0+ Thumb - C flag Started 18 hours ago by Sean Dunlevy 0 replies 91 views
Suggested answer CPSR status back to C variable Latest yesterday by Frost13 3 replies 2531 views
Suggested answer Is pre-compiled ARM9 libs able to run on an ARM11 chip Latest 2 days ago by Andy Neil 4 replies 1826 views