IEEE

Cognitive Radio Spectrum Sensing on the Edge: A Quantization-Aware Deep Learning Approach

Abstract: Wideband spectrum sensing demands ultra-low latency and high accuracy to detect spectrum holes, yet deploying deep learning (DL)-based models on resource-constrained edge devices is ...
IEEE

Efficient Hierarchical Quantization for Heterogeneous Devices in Cloud–Edge–Device Architecture

Abstract: Cloud-based quantization is a key technique for deploying deep neural networks on resource-constrained devices. However, the growing number of heterogeneous devices has placed an increasing ...
Microsoft

SNRAware: Improved Deep Learning MRI Denoising with SNR Unit Training and G-factor Map Augmentation

To develop and evaluate a new deep learning MR denoising method that leverages quantitative noise distribution information from the reconstruction process to improve denoising performance and ...
Microsoft

From awareness to action: Building a security-first culture for the agentic AI era

The insights gained from Cybersecurity Awareness Month, right through to Microsoft Ignite 2025, demonstrate that security remains a top priority for business leaders. It serves as a strategic lever ...