Техническая документация
Характеристики
Brand
CoralТип продукции
Инструмент разработки микроконтроллера
Классификация комплектов
Плата микроконтроллера
Наименование комплекта
Dev Board Micro
Технология
ARM Cortex
Сердечник устройства
ARM Cortex-M7
Название семейства процессоров
ARM
Артикул процессора
i.MX RT1176
Тип процессора
Микроконтроллер
Стандарты/одобрения
Нет
Страна происхождения
China
Информация о товаре
The Coral Dev Board Micro is a microcontroller board that benefits from a built-in camera,microphone, and Coral Edge TPU, allowing you to quickly prototype and deploy low-power embedded systems with on-device ML inferencing.
By combining the Cortex M4 and M7 processors with the Coral Edge TPU on this board, you can design systems that cascade from extreme low-power ML inferencing to more complex—yet still power-efficient—ML inferencing.
You can also expand the hardware with custom add-on boards using the high-density board-to-board connectors. The Edge TPU is a small ASIC designed by Google that accelerates tensor flow lite models in a power efficient manner. One Edge TPU is capable of performing 4 trillion operations per second. This on-device ML processing reduces latency, increases data privacy, and removes the need for a constant internet connection.
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Техническая документация
Характеристики
Brand
CoralТип продукции
Инструмент разработки микроконтроллера
Классификация комплектов
Плата микроконтроллера
Наименование комплекта
Dev Board Micro
Технология
ARM Cortex
Сердечник устройства
ARM Cortex-M7
Название семейства процессоров
ARM
Артикул процессора
i.MX RT1176
Тип процессора
Микроконтроллер
Стандарты/одобрения
Нет
Страна происхождения
China
Информация о товаре
The Coral Dev Board Micro is a microcontroller board that benefits from a built-in camera,microphone, and Coral Edge TPU, allowing you to quickly prototype and deploy low-power embedded systems with on-device ML inferencing.
By combining the Cortex M4 and M7 processors with the Coral Edge TPU on this board, you can design systems that cascade from extreme low-power ML inferencing to more complex—yet still power-efficient—ML inferencing.
You can also expand the hardware with custom add-on boards using the high-density board-to-board connectors. The Edge TPU is a small ASIC designed by Google that accelerates tensor flow lite models in a power efficient manner. One Edge TPU is capable of performing 4 trillion operations per second. This on-device ML processing reduces latency, increases data privacy, and removes the need for a constant internet connection.