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Artigo n.º:
229165007
USB Edge TPU ML Accelerator Coprocessor for Raspberry Pi and Other Embedded Single Board Computers
88% of respondents would recommend this to a friend
Artigo n.º:
229165007
STD 4576780
Detalhes do Preço
Excluindo custos de envio e alfandegários ( Os custos de envio e alfandegários serão calculados na finalização da compra )
*Todos os artigos serão importados de EU
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Importado da loja EU
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Encomende já e receba por volta de Sexta-Feira, Setembro 18
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Os nossos principais Parceiros Logísticos
Coral USB Accelerator provides high performance ML inferencing with a low power cost over a USB 3.0 interface.
Fast
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Devolução
gratuita*
Embalagem Segura
Produtos 100% Originais
Certificação PCI DSS
Certificação ISO 27001
O que se Destaca
Edge AI Processing
Accelerates machine learning tasks on embedded systems, enabling quick model inference and reduced latency for complex applications.
Seamless Integration
Easily connects to Raspberry Pi and other single-board computers, simplifying the implementation of AI in various tech projects.
Energy Efficient
Designed for low power consumption, allowing for high-performance operations without draining power, making it ideal for IoT devices.
Detalhes do produto
- Featuring the Edge TPU, designed and built by Google
- Provides high performance ML inferencing with low power cost over a USB 3.0 interface
- Executes state-of-the-art mobile vision models at over 100 fps in a power-efficient manner
- Allows fast ML inferencing to embedded AI devices in a power-efficient and privacy-preserving way
- Models developed in TensorFlow Lite and then compiled to run on the USB Accelerator
- Key benefits: High speed TensorFlow Lite inferencing, low power, small footprint
| RAM Memory Installed | 2 KB |
| Memory Storage Capacity | 16 KB |
| Processor Speed | 32 MHz |
| Network Connectivity Technology | USB |
| Operating System | Linux |
| Processor Brand | ARM |
| Compatible Devices | PC, Laptop, Raspberry Pi, Other Linux Devices |
| RAM Memory Technology | LPDDR |
| Processor Count | 1 |
| Total USB Ports | 1 |
| Item Dimensions L x W x H | 7.6L x 5.1W x 2.5H centimetres |
| Brand Name | Google Coral |
| Model Name | Coral USB Accelerator |
| Number of Items | 1 |
| UPC | 608614201389 |
| Unit Count | 1.0 stu00fcck |
| Manufacturer | Google Coral |
| Model Number | Coral-USB-Accelerator |
| Manufacturer Part Number | Coral-USB-Accelerator |
| Brand | Google Coral |
| RAM memory installed size | 2 KB |
| CPU speed | 32 MHz |
| Country of Origin | This item will be imported from EU |
| What is in the box | USB Edge TPU ML... For more details, please check description/product details |
Quem Deverá Comprar?
-
Machine Learning Enthusiasts
Ideal for hobbyists experimenting with machine learning projects on Raspberry Pi due to its high processing capability.
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Developers and Engineers
Perfect for developers needing fast inference for AI applications in embedded systems and prototypes.
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IoT Solutions Designers
Great for those building IoT applications that require edge computing for real-time data processing.
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Casual Users
Not suitable for casual users with no technical background or experience in machine learning and programming.
DESCRIÇÃO DO PRODUTO
USB Edge TPU ML Accelerator Coprocessor for Raspberry Pi and Other Embedded Single Board Computers
About This Item
Introducing the Google Coral USB Edge TPU ML Accelerator - the ultimate coprocessor for Raspberry Pi and other embedded single board computers. This powerful device brings advanced machine learning (ML) inferencing capabilities to your existing Linux systems. Featuring the highly efficient Edge TPU, a small ASIC designed and developed by Google, the Coral USB Accelerator provides you with high-performance ML inferencing while consuming minimal power through a USB 3.0 interface. With its cutting-edge technology, this accelerator can execute state-of-the-art mobile vision models, such as MobileNet v2, at over 100 frames per second in a power-efficient manner. The Coral USB Accelerator allows you to enable fast ML inferencing on your embedded AI devices, all while maintaining a power-efficient and privacy-preserving approach.
Models are developed using TensorFlow Lite and then compiled to run seamlessly on this accelerator, providing you with high-speed inferencing capabilities. One of the key benefits of the Edge TPU is its ability to deliver low-power ML inferencing without compromising on performance. This coprocessor is equipped with an Arm 32-bit Cortex-M0+ Microprocessor (MCU) with up to 32 MHz clock speed, ensuring outstanding speed and efficiency. In addition to its impressive performance, the Coral USB Accelerator also boasts a small footprint, making it a flexible and versatile solution for your embedded systems. It comes with a USB 3.1 (gen 1) port and cable, ensuring a SuperSpeed data transfer rate of up to 5Gb/s. The Coral USB Accelerator is fully compatible with Google Cloud and supports Debian Linux on host CPUs.
You can develop models using TensorFlow and take advantage of its compatibility with popular architectures like MobileNet and Inception. Furthermore, the device supports custom architectures, opening up endless possibilities for your ML projects. At Ubuy, we offer a range of e-commerce options for Raspberry Pi and other embedded single board computers, allowing you to conveniently shop for high-quality embedded computing products and components. Whether you are an AI enthusiast, a hobbyist, or a professional developer, our online store provides you with a seamless shopping experience for all your embedded system needs. Discover the future of embedded AI with the Google Coral USB Edge TPU ML Accelerator.
Shop now and unlock the potential of your embedded systems!.
Tem alguma Dúvida? Converse connosco
Perguntas e respostas do cliente
-
Pergunta:
What is the Edge TPU?
Resposta: The Edge TPU is a small ASIC designed and built by Google that provides high performance ML inferencing with a low power cost over a USB 3.0 interface. -
Pergunta:
Which models does the Coral USB Accelerator support?
Resposta: It fully supports MobileNet and Inception architectures though custom architectures are possible. -
Pergunta:
What is included in the package?
Resposta: The package includes the Coral USB Accelerator and a USB Type-C to Type-A cable.
GoogleCoral USB Cables Coral-USB-Accelerator Editorial Review
USB Edge TPU ML Accelerator Coprocessor For Raspberry Pi And Other Embedded Single Board Computers is an essential upgrade for optimizing machine learning applications on Raspberry Pi systems. Users report a significant performance boost, particularly in AI tasks such as object detection, while the compact design ensures easy integration with existing setups. The installation process is straightforward, allowing users to quickly connect via USB without complex configurations. The device provides efficient CPU load management, making it ideal for continuous use in projects like local camera surveillance and image recognition. Overall, it supports various compatible devices and plays well with popular software like Home Assistant and Frigate, enhancing local AI processing capabilities.
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Prós
- Compact design fits well with small projects
- Easy installation via USB connection
- Significantly reduces CPU workload
- Compatible with multiple Linux devices
- Excellent for AI and image recognition
- Stable performance even under continuous use
Contras
- Requires compatible software for optimal function
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STD 4576780
Encomende já e receba por volta de Sexta-Feira, Setembro 18
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Em conformidade com a norma PCI DSS e com certificação ISO 27001:2022, com pagamentos encriptados e proteção total do comprador em todas as encomendas.
Os nossos principais Parceiros Logísticos
Entrega internacional mais rápida
Recursos e benefícios
- Brings powerful ML inferencing capabilities to existing Linux systems
- Execute state-of-the-art mobile vision models in a power-efficient manner
- Great for fast ML inferencing to embedded AI devices in a privacy-preserving way
- Fully supports MobileNet and Inception architectures though custom architectures are possible
- Compatible with Google Cloud
- Features Google Edge TPU ML accelerator coprocessor, USB 3.0 Type-C socket, Debian Linux on host CPU and models built with TensorFlow
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