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    Seeed Edge AI Device with Jetson-10-1-H0 with Nvidia Jetson Nano 4GB Module M.2 Key E Slot, Type-C connectors, Aluminium case, p

    FJ $804.34 excl. VAT

    Seeed Edge AI Device with Jetson-10-1-H0 with Nvidia Jetson Nano 4GB Module M.2 Key E Slot, Type-C connectors, Aluminium case, pre-installed JetPack System

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    Development & Expansion Boards

    Description

    Note: We have already installed JetPack 4.6 system in the reComputer and you can directly use it by powering in.
    Note: A 3V RTC battery (CR1220)is included! Please install it by yourself!

    Features

    - Hand-size edge AI device built with NVIDIA Jetson Nano Production Module, delivering 128 NVIDIA CUDA® cores delivers 0.5 TFLOPs (FP16). - Nearly the same design as Jetson Nano Developer Kit's reference carrier board, rich IOs including Gigabit Ethernet port, USB 3.0 & USB 2.0 ports, HDMI port. - Pre-installed NVIDIA official JetPack software, ready for cloud-native application. - Support a wide range of AI applications fast building with our ecosystem partners. - Support Allxon to enable secure remote device management. - Able to mount on the wall with mounting holes on the back.
    Description
    reComputer Jetson series are compact edge computers built with NVIDIA advanced AI embedded systems: Jetson-10 (Nano 4GB) and Jetson-20 (Xavier NX). With rich extension modules, industrial peripherals, thermal management, reComputer Jetson is ready to help you accelerate and scale the next-gen AI product by deploying popular DNN models and ML frameworks to the edge and inferencing with high performance, for tasks like real-time classification and object detection, pose estimation, semantic segmentation, and natural language processing (NLP).
    Jetson Nano: Deep Learning Inference Performance

    Reference: NVIDIA, Performance of various deep learning inference networks with Jetson Nano and TensorRT, using FP16 precision and batch size 1
    Developers can use highly accurate pre-trained models from TAO Toolkit and deploy with DeepStream. Jetson Nano can achieve 11 FPS for PeopleNet- ResNet34 of People Detection, 19 FPS for DashCamNet-ResNet18 of Vehicle Detection, and 101 FPS for FaceDetect-IR-ResNet18 of Face Detection. Benchmark details can be found on NVIDIA®'s DeepStream SDK website.
    Jetson Nano can run a wide variety of advanced networks, including the full native versions of popular ML frameworks like TensorFlow, PyTorch, Caffe/Caffe2, Keras, MXNet, and others.
    reComputer Jetson series is compatible with the entire NVIDIA Jetson software stack, industry-leading AI frameworks, development platforms like Edge Impulse, AlwaysAI, and cloud-based robot development tool Nimbus.
    Application: next-gen autonomous machine at the edge
    reComputer Jetson series is ideal for building autonomous machines and complex AI system tasks of image recognition, object detection and localization, pose estimation, semantic segmentation, video processing, and intelligent analytics.
    Edge AI into the Wild: UAV, Drone, Wildlife protection, Agriculture
    Smart City: Traffic, Retail, Healthcare Industry 4.0: Manufacturing, Logistics, Delivery, Service

    Prebuild system for edge AI integration
    All NVIDIA® Jetson™ modules and developer kits are supported by the same software stack, enabling you to develop once and deploy everywhere. Jetson Software is designed to provide end-to-end acceleration for AI applications and accelerate your time to market. We bring the same powerful NVIDIA technologies that power data center and cloud deployments to the edge.
    NVIDIA JetPack includes NVIDIA Container Runtime with Docker integration, enabling GPU accelerated containerized applications on Jetson platform. Jetpack also brings support for NVIDIA Triton™ Inference Server to simplify the deployment of AI models at scale.

    NVIDIA Jetson powered Edge AI platform at Seeed
    At Seeed, you will find everything you want to work with NVIDIA Jetson Platform - official NVIDIA Jetson Dev Kits, Seeed-designed carrier boards, and edge devices, as well as accessories. Seeed will continue working on the Jetson product line and will be ready to combine our partners' unique technology with Seeed's hardware expertise for an end-to-end solution.
    Hardware specification Comparison among reComputer Jetson-10 series and Official Dev Kits

    Interface-rich reference carrier board
    Nearly the same functional design as Jetson Nano 2GB Developer Kit
    Seeed reference carrier board for Jetson-10-1-A0 is a high-performance, interface rich NVIDIA Jetson Nano compatible carrier board, providing HDMI 2.0, Gigabit Ethernet, USB 3.0, USB 2.0, CSI camera, GPIO, I2C, I2S, fans, and other rich peripheral interfaces. It has nearly the same functional design and size as the carrier board of Nvidia Jetson Nano 2GB Developer Kit | NVIDIA Developer. Take advantage of the small form factor, sensor-rich interfaces, and big performance to bring new capability to all your embedded AI and edge systems.

    Desktop, Wall Mount, or fit in anywhere
    With an overall dimension of 130mm*120mm*50mm, it is only around 1/10 of the size of an ordinary computer case which makes it possible to fit in edge AI scenarios. The back screw holes allow you to hang the product as you need. We also provide other editions case like blue, silver and silver mental, whose stackable structure allows you to stack more middle layers to create rooms very easily.





    Manufacturer
    Seeed
    Product No.
    110061361
    Items included
    - 1 x Acrylic Cover - 1 x Aluminium Frame - 1 x Jetson Nano module - 1 x Heatsink - 1 x Carrier board - 1 x 12V/2A Power Adapter (with 5 interchangeable adapter plugs)


    Manufacturer Part No:

    110061361
    Brand:

    Seeed

    Product Type:

    -
    UPC

    -
    Product Family:

    Edge AI Device with
    Shipping Weight:

    1 kg
    PB Part No:

    SBCSED0031
    Product Model:

    Jetson-10-1-H0



    Warranty:
    12 months *
    * Warranty period is as stated above unless the manufacturer has chosen to specify a longer period.
    All warranties are return to base unless otherwise specified.

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