A must-have accessory pack for the Kria KV260 Vision AI Starter Kit
KV260 Vision AI Starter Kit shown for representation purposes, NOT INCLUDED in the Basic Accessory Pack
AC/DC WALL MOUNT ADAPTER 12V 36W
Plugs into the DC power supply jack on the Starter Kit. Comes with interchangeable blades for major regions (North America, Europe, UK, Australia, China)
Connects user end system (USB-A) to the micro-B connector on the starter kit to establish UART connection to setup the terminal
Connects the user’s networking setup to the RJ-45 connector on the Starter Kit
Connects the HDMI connector on the Starter Kit to an HDMI monitor/display
One 16/32/64GB MicroSD card and adapter to flash the SD card image to boot or run applications
Part of the ON Semiconductor IAS family of modules. 1/3.2” CMOS Sensor (AR1335)
Connects to the 2 IAS connectors of the Starter Kit
The KV260 is a fully featured evaluation kit capable of leveraging pre-built accelerated applications to quickly develop unique solutions for production deployment on the K26 SOM.
Step-by-Step Guide to Get Up and Running
Kria™ adaptive System-on-Module (SOM) devices from AMD play an important role in electric drive control. They can optimize performance, help a motor run more efficiently, reduce power consumption, mitigate noise, cut vibration, and detect potential failures before they happen. Download our new motor control eBook to learn more!
Learn all about adaptive SOMs, including examples of why and how they can be deployed in next-generation edge applications, and how smart vision providers benefit from the performance, flexibility, and rapid development that can only be achieved by an adaptive SOM.
Demand for robotics is accelerating rapidly. Building a robot that is designed to be safe and secure and can operate alongside humans is difficult enough. But getting these technologies working together can be even more challenging. Complicating matters is the addition of machine learning and artificial intelligence, which is making it more difficult to keep up with computational demands.
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