Webinar

Image Detection with M5Stack UnitV2

A High Performance AI-Enabled Camera Based on Teeny-Tiny Linux

Implement image detection and image classification applications like never before with M5Stack's newest high-performance AI image recognition camera, UnitV2. This concise and efficient camera runs on Linux and offers a dual training mode for rapid prototyping. 


In this webinar, you'll learn more about the features and capabilities of the UnitV2 and how to create your own image recognition applications out of the box. 

May 13, 20216PM PDT

May 14, 20219AM GMT+8

This 1- hour webinar will include:

  • The most important features of the M5Stack UnitV2.
  • How to more effectively build projects with higher accuracy using M5Stack's AI Module Training Service (V-Training).
  • Modern IoT applications for a variety of scenarios.
  • Recognition demo showcasing the UnitV2 out of box capabilities

UnitV2

M5Stack UnitV2 is a high-performance AI image recognition module that offers a new way for engineers to quickly implement image detection and image classification. It is the first M5Stack product that runs on the Linux operating system.


Features

  • CPU: SigmaStar SSD202D, Dual Cortex-A7 1.2 Ghz Processor
  • RAM & Flash: 256MB DDR3, 512MB NAND Flash
  • Image Sensor: GC2145 1080P Colored Sensor, FOV 68° Minimum Focusing distance = 60cm
  • WiFi: 150Mbs 2.4GHz 802.11 b/g/n WiFi
  • Peripherals: Microphone, TF Card, UART
  • OS: Linux

Jimmy Lai

CEO/Founder, M5Stack

Jimmy Lai is an experienced engineer who, through years of creating software and hardware for the booming tech industry in Asia, saw gaps in the market. Jimmy was driven to provide a better solution to fill the gap between a development board and an end product for other engineers like himself and began to design and create a series of 5cm x 5cm modular stackable prototypes in 2016.

Han Xiao

Engineer, M5Stack

Han Xiao is a senior engineer of M5Stack. During the past few years his work has focused upon developing V-Training module training and UnitV2 hardware design.

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