posted by @rayz

PDF] System and method for real-time radar-based action recognition using spiking neural network (snn)

DEY Sounak, A Mukherjee, D Banerjee, R Smriti… - US Patent App. 17/122,041, 2021

This disclosure relates generally to action recognition and more particu larly to system and method for real-time radar-based action recognition. The classical machine learning techniques used for learning and inferring human actions from …

Sounak Dey and Arijit Mukherjee listed on this patent have a direct link to Brainchip via Tata consultancy services (TCS) having co authored a paper with Gilles Bezard and Douglas Mclelland from Brainchip in 2019. (See below)
Therefore, they along with TCS are well versed with what Brainchip have to offer.

https://brainchipinc.com/brainchip-and-tata-consultancy-services-tcs-jointly-present-a-demonstration-featuring-its-akida-neuromorphic-technology-platform-at-neurips-2019/

BrainChip And Tata Consultancy Services (TCS) Jointly Present A Demonstration Featuring Its Akida Neuromorphic Technology Platform At NeurIPS 2019

Company to demonstrate hand gesture recognition using DVS spiking input on the Akida Neuromorphic Technology Platform at leading industry conference

SAN FRANCISCO–(BUSINESS WIRE)– BrainChip Holdings Ltd. (ASX: BRN), a leading provider of ultra-low power, high performance edge AI technology, today announced that it has been accepted to present a demonstration featuring its Akida™ Neuromorphic System-on-Chip Technology, recognizing and classifying hand gestures from the audience at the 33^rd Conference on Neural Information Processing Systems (NeurIPS), at the Vancouver Convention Center in Vancouver, Canada.

The paper titled “Human Gesture Recognition using Spiking Input on Akida Neuromorphic Platform” co-authored by Sounak Dey, Arijit Mukherjee from TCS Research at Tata Consultancy Services (TCS) and Gilles Bézard, Douglas McLelland from BrainChip will be presented. The demonstration will involve capturing a few hand gestures and hand positions from the audience using a Dynamic Vision Sensor camera and performing live learning and classification using the Akida neuromorphic

. This will showcase the fast and lightweight unsupervised live learning capability of the spiking neural network (SNN) and the Akida neuromorphic chip, which takes much less data than a traditional deep neural network (DNN) counterpart, consuming much less power during training.

Akida is available as a licensable IP technology that can be integrated into ASIC devices and will be available as an integrated SoC, both suitable for applications such as surveillance, advanced driver assistance systems (ADAS), autonomous vehicles (AV), vision guided robotics, drones, augmented and virtual reality (AR/VR), acoustic analysis, and Industrial Internet-of-Things (IoT). Akida performs neural processing and memory accesses on the edge, which vastly reduces the computing resources required of the system host CPU. This unprecedented efficiency not only delivers faster results, it consumes only a tiny fraction of the power resources of traditional AI processing. Functions like training, learning, and inferencing are orders of magnitude more efficient with Akida.

“While the recognition of a simple hand gesture might at first seem simple, it is in fact quite a revolutionary advance in the state of today’s human and robot interactive environments,” said Roger Levinson, COO of BrainChip. “We are pleased to have the opportunity to showcase the extent of this revolutionary advance at NeurIPS and are eager to show how an Akida-based platform can be utilized to ingest imagery, train the system to recognize what it has seen and learn in a way that is vastly more efficient and accurate than what other solutions have been able to achieve thus far.”

TT