Artificial Intelligence | News | Insights | AiThority
[bsfp-cryptocurrency style=”widget-18″ align=”marquee” columns=”6″ coins=”selected” coins-count=”6″ coins-selected=”BTC,ETH,XRP,LTC,EOS,ADA,XLM,NEO,LTC,EOS,XEM,DASH,USDT,BNB,QTUM,XVG,ONT,ZEC,STEEM” currency=”USD” title=”Cryptocurrency Widget” show_title=”0″ icon=”” scheme=”light” bs-show-desktop=”1″ bs-show-tablet=”1″ bs-show-phone=”1″ custom-css-class=”” custom-id=”” css=”.vc_custom_1523079266073{margin-bottom: 0px !important;padding-top: 0px !important;padding-bottom: 0px !important;}”]

Gyrfalcon White Paper Examines New AI Chipsets for Edge-Vision Computing

Gyrfalcon Technology announced a new white paper entitled “AI-Powered Camera Sensors: Computing at the Edge – Smart Cameras, Robotic Vehicles and End-Point Devices.” Artificial Intelligence (AI) processing on the edge device – particularly AI vision-specific industries – eliminates privacy concerns, while avoiding the speed, bandwidth, latency, power consumption and cost issues of cloud computing.

Recommended AI News: Nokia Digitalizes 100 Percent of Global 5G Network Deployments

The white paper is available for free here.

“The emerging smart CMOS image sensors technology trend is to merge ISP functionality and deep learning network processor into a unified end-to-end AI co-processor,” said Dr. Manouchehr Rafie, Vice President of Advanced Technologies at Gyrfalcon. “This white paper defines a new paradigm for on-device integrated AI-camera sensor co-processor chips. The chips’ built-in high-processing power and memory allow the machine- and human-vision applications to operate much faster, more energy-efficiently, cost-effectively and securely without sending any data to remote servers.”

Related Posts
1 of 14,063

Recommended AI News: Brain Corp Names Technical Visionary and AI Leader Jon Thomason as Chief Technology Officer

This white paper explores how an integrated edge AI Gyrfalcon co-processor chip into a camera module can produce real-time images and video streams that are superior to some of the existing high-end and expensive smartphones. AI-powered camera sensors offer distinct advantages over standard cameras by performing not just capturing the enhanced images, but also performing image analysis, content-aware and event/pattern recognition, all in one compact system. An integrated AI image co-processor chip into a camera module can directly use raw data from the sensor output to produce DSLR-quality images as well as highly accurate computer vision results.

This white paper also explains why smartphones and automotive are the dominant drivers due to their fastest growth and largest volume shipment and revenue in edge vision computing. The mobile phone market segment alone is forecast to account for over 50% of the 2025 global edge AI chipset market, according to Omdia | Tractica.  

Recommended AI News: LMS365 Transforms Compliance, Security and Technology Training for Government Sector

Leave A Reply

Your email address will not be published.