ML-examples VS CMSIS-NN

Compare ML-examples vs CMSIS-NN and see what are their differences.

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ML-examples CMSIS-NN
2 1
406 148
2.2% 5.4%
5.0 8.0
9 months ago 7 days ago
C++ C
Apache License 2.0 Apache License 2.0
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

ML-examples

Posts with mentions or reviews of ML-examples. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-11-14.

CMSIS-NN

Posts with mentions or reviews of CMSIS-NN. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-11-14.

What are some alternatives?

When comparing ML-examples and CMSIS-NN you can also consider the following projects:

MNN - MNN is a blazing fast, lightweight deep learning framework, battle-tested by business-critical use cases in Alibaba

nnom - A higher-level Neural Network library for microcontrollers.

oneflow - OneFlow is a deep learning framework designed to be user-friendly, scalable and efficient.

onnx2c - Open Neural Network Exchange to C compiler.

tensorflow - An Open Source Machine Learning Framework for Everyone

cONNXr - Pure C ONNX runtime with zero dependancies for embedded devices

deepC - vendor independent TinyML deep learning library, compiler and inference framework microcomputers and micro-controllers

CNTK - Microsoft Cognitive Toolkit (CNTK), an open source deep-learning toolkit

tinyengine - [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 256KB Memory

TinyMaix - TinyMaix is a tiny inference library for microcontrollers (TinyML).