A neural interface framework integrating L2 regularization with attention supervision paradigms achieves 96.87% classification accuracy in EEG ...

Learn how the Inception Net V1 architecture works and how to implement it from scratch using PyTorch. Perfect for deep ...

Abstract: This paper investigates the routing problem in the mega low earth orbit (mLEO) satellite constellations considering factors including distribution of the users, topology of the networks and ...

AI in Computer-Aided Synthesis Planning Market reached USD 2.13 bn in 2024 and is expected to grow rapidly to USD 68.06 bn by ...

The NASP platform utilises trained neural networks in the analogue domain to perform AI inference with exceptionally lower power consumption compared to conventional digital neural processors.

Using single-cell RNA sequencing and genetic screening, the researchers identified key surface proteins that mediate ...

Abstract: Predicting remaining useful life (RUL) plays a crucial role in the prognostics and health management of industrial systems that involve a variety of interrelated sensors. Given a constant ...

This valuable study uses EEG and computational modeling to investigate hemispheric oscillatory asymmetries in unilateral spatial neglect. The work benefits from rare patient data and a careful ...

Polyn’s NASP technology and design tools give semiconductor and AI developers a new way to quickly implement neural networks directly in analogue silicon. It offers process-agnostic design across ...

Polyn will demonstrate its ultra-low-power neuromorphic analog signal processing (NASP) chip for edge AI applications at CES ...