How To Make Cybersecurity Training Actually Stick

Cybersecurity training is most effective when it isn’t just another box to check but is practical, relevant and worth ...
IEEE

On-Device Training of Fully Quantized Deep Neural Networks on Cortex-M Microcontrollers

Abstract: On-device training of deep neural networks (DNNs) allows models to adapt and fine tune to newly collected data or changing domains while deployed on microcontroller units (MCUs). However, ...
GitHub

kentaroy47/vision-transformers-cifar10

This is your go-to playground for training Vision Transformers (ViT) and its related models on CIFAR-10/CIFAR-100, a common benchmark dataset in computer vision. The whole codebase is implemented in ...
IEEE

A Survey of Stochastic Computing Neural Networks for Machine Learning Applications

Abstract: Neural networks (NNs) are effective machine learning models that require significant hardware and energy consumption in their computing process. To implement NNs, stochastic computing (SC) ...