System und Verfahren zur Echtzeitradarbasierten Aktionserkennung unter Verwendung von Neuronalen Spiking-Netzen (snn)

Details

Veröffentlichungs-Nr.

EP3913534

Aktenzeichen

EP20213433

Anmeldetag

11. Dezember 2020

Veröffentlichung

22. November 2023

Erteilung

22. November 2023

Rechtsraum

EP

IPC

G06V10/44G06V10/82G06V40/20

Abstract

This disclosure relates generally to action recognition and more particularly to system and method for real-time radar-based action recognition. The classical machine learning techniques used for learning and inferring human actions from radar images are compute intensive, and require volumes of training data, making them unsuitable for deployment on network edge. The disclosed system utilizes neuromorphic computing and Spiking Neural Networks (SNN) to learn human actions from radar data captured by radar sensor(s). In an embodiment, the disclosed system includes a SNN model having a data pre-processing layer, Convolutional SNN layers and a Classifier layer. The preprocessing layer receives radar data including doppler frequencies reflected from the target and determines a binarized matrix. The CSNN layers extracts features (spatial and temporal) associated with the target's actions based on the binarized matrix. The classifier layer identifies a type of the action performed by the target based on the features

Anmelder

Firma

Tata Consultancy Services Limited

Land

🇮🇳 Indien

Fachgebiete