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[NeurIPS 2020] MCUNet: Tiny Deep Learning on IoT Devices; [NeurIPS 2021] MCUNetV2: Memory-Efficient Patch-based Inference for Tiny Deep Learning; [NeurIPS 2022] MCUNetV3: On-Device Training Under 256K...

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Anyone knows that how to entegrate this engine to OpenMV H7 Plus board ?

Thanks for the great work. Unfortunately, as of now the library only works for mcunet models. The support for custom models is not completely implemented. For example, to convert a...

Is it possible to capture/improve the performance of (in terms of **accuracy** and **peak memory usage**) a **custom tflite** already trained model (that I converted from an originally simple keras...

Thanks for the great work. As the tutorial described, the input and output are all of "int8" type. Is uint8 model supported or we should just convert into int8 instead?...

Hi, Where do I find jupyter notebook of given example visual wake word (VWW) model in the tutorial folder if I want to check it's model architecture and how it...

thanks for your excellent jobs! it's very useful for me to porting ai model on low power edge devices. i'm very interesting about the patch inference method, but i can't...

We're trying to run NAS ourselves using OFA, but you have not open-sourced up-to-date ProxylessNAS models used in the mcunet search. These would be helpful for us to re-create your...

Excuse me, I cannot trace the exact definition of the following api which are related to op layermem["MAC"] = op.get_macs() layermem["activation"] = op.get_activation_size() layermem["scale"] = op.get_scale_size() layermem["runtime"] = op.get_sbuf_size() layermem["kernel"]...

Thanks for the great work! Currently I do not use ArduCam and I just want to test LCD After following steps described in the tutorial, I can compile without errors...

Tinyengine is an exciting project to people want to deploy ai models on mcus like me . I think tinyengine would enable deep learning on huge amounts of edge devices...