Gallery nn model

CMSIS-NN is a collection of efficient neural network kernels developed to maximize the performance and minimize the memory footprint of neural networks on Arm Cortex-M processor cores targeted for intelligent IoT edge devices. Cookies and similar technologies enable us to provide you with an optimized user experience and functionality of our website. Real-world applications of AI and machine Dropout is a regularization technique proposed by Geoff Hinton that randomly sets activations in a neural network to 0 with a probability of pp. This collection of neural network kernels was developed to decrease the amount of memory used on Arm Cortex-M processor cores by neural networks on IoT edge devices. It is an industry wide software library for the ARM Cortex microcontroller.