Deep Neural Networks are becoming increasingly popular in always-on endpoint devices. Developers can perform data analytics right at the source, with reduced latency as well as energy consumption. During this talk, we will introduce how Tensorflow Lite for Microcontrollers (TFLu) and its integration with CMSIS-NN will maximize the performance of machine learning applications. Developers can now run larger, more complex neural networks on Arm MCUs and micro NPUs while reducing memory footprint and inference time.
tinyML development with Tensorflow Lite for Microcontrollers using CMSIS-NN