Memory-Efficient Patch-based Inference for Tiny Deep Learning on Microcontrollers

Patch-based inference scheduling can significantly reduce the peak memory usage of convolutional neural networks by up to 8x, enabling larger input resolutions and model capacities on microcontrollers.