“MAX78000 AI microcontroller and Xailient’s Detectum neural network detects and localizes faces in video and images at just 12ms per inference
Maxim Integrated Products, Inc. (NASDAQ: MXIM) and Xailient Inc., a company focused on artificial intelligence (AI) for the edge, today announced that Maxim Integrated’s MAX78000 ultra-low power neural-network microcontroller detects and localizes faces in video and images using Xailient’s proprietary Detectum™ neural network. Xailient’s neural network draws 250x lower power (at just 280 microJoules) than conventional embedded solutions, and at 12 milliseconds (ms) per inference, the network performs in real time and is faster than the most efficient face-detection solution available for the edge.
Battery-powered AI systems that require face detection, such as home cameras, industrial grade smart security cameras and retail solutions, require a low-power solution to provide the longest possible operation between charges. In addition to supporting standalone applications, Maxim Integrated’s microcontroller paired with Xailient’s neural network improves overall power efficiency and battery life of hybrid edge/cloud applications that employ a low-power ‘listening’ mode which then awakens more complex systems when a face is detected.
Xailient’s Detectum neural network includes focus, zoom and visual wake-word technologies to detect and localize faces in video and images at 76x faster rates than conventional software solutions, at similar or better accuracy. In addition, the flexible network can be extended to applications other than facial recognition, such as livestock inventory and monitoring, parking spot occupancy, inventory levels and more.
Longest Battery Life/Highest Energy Efficiency: Xailient’s neural network optimizes the computational efficiency and flexible low-power sleep modes offered by Maxim Integrated’s ultra-low power MAX78000 microcontroller. Together, the products extend the operating time of coin cell battery-powered, hybrid edge/cloud applications for many years.
Fastest Inference Speed for Improved Accuracy: Speed is a significant factor for AI because with faster inferencing, you can react in real time or quickly average multiple inferences to improve accuracy. Detecting faces in an image in just 12ms provides that flexibility between response time and accuracy.”