Neural network detects faces in 12milliseconds

Faces can be detected in video and still images at 12 milliseconds per inference in the Detectum neural network created by Xailient. The IoT face detection system uses Maxim Integrated’s MAX78000 AI microcontroller.

Xailient’s neural network draws 250 times  lower power (at just 280 microJoules) than conventional embedded solutions, and at 12 milliseconds per inference, the network performs in real time and is faster than the most efficient face-detection system available for the edge, claims Maxim.

Battery-powered AI systems that require face detection, such as home cameras, industrial grade smart security cameras and retail solutions, require a low power operation to provide the longest possible time 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 use a low power ‘listening’ mode which wakes up the more complex systems when a face is detected.

Xailient’s Detectum neural network includes focus, zoom and visual wake word technologies to detect and localise faces in video and images at 76 times faster rates than conventional software, at similar or better accuracy, says Maxim. The ability to localise a face means that it can be used for advanced applications which determine where a face is in the image’s field of view. Examples include person, vehicle and object counting, presence or obstruction detection, as well as path mapping and footfall heatmaps.

The network can be extended to other applications such as livestock inventory and monitoring, parking spot occupancy and retail or warehouse inventory levels.

Xailient’s neural network combined with the computational efficiency and low power sleep modes of the MAX78000 microcontroller extend the operating time of coin cell battery-powered, hybrid edge/cloud applications for many years, says Maxim.

“AI is on track to be the second largest carbon emitting industry,” said Dr. Shivy Yohanandan, Xailient chief technology office (CTO) and inventor of Xailient’s Detectum neural network technology. “Replacing 14 legacy internet protocol cameras that use traditional cloud AI with edge-based cameras equipped with the Maxim Integrated MAX78000 paired with Xailient’s neural network has the equivalent carbon impact of taking one gasoline powered car off the road,” he said.

The MAX78000 is available now and Maxim also offers the MAX78000EVKIT# evaluation kit.

The Detectum neural network, series models, tools, services as well as focus, zoom and visual wake word technologies are available directly from Xailient.

http://www.maximintegrated.com

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Eight-channel ReDriver has PCIe 4.0 interfaces

Extending its linear ReDriver ICs, Diodes has added the PI3UPI1608 with internal coupling capacitors. The IC can “significantly” extend PCB trace lengths while minimising power consumption and associated bill of materials costs, says the company.

It supports speeds of up to 20Gbits per second and is UPI 2.0 and PCIe 4.0- compliant with eight differential channels. Integral coupling capacitors save board area by reducing the number of external components required. can be avoided.

Key applications include AI servers, data storage equipment, 5G networking infrastructure and high-performance PCs as well as CPU-to-CPU and CPU-to-storage interconnects.

The PI3UPI1608 ReDriver compensates for channel losses at the transmitter and improves signal integrity at the receiver. It is also optimised for high-performance systems operating at elevated frequencies.

The programmable linear equalisation, output swing, and flat gain capabilities enable the PI3UPI1608 to reduce bit error rates (BERs) and lower intersymbol interference. Programmability can be carried out via the pin strap and I2C interface.

The PI3UPI1608 ReDriver IC runs off a 3.3V supply and has an operating temperature range of -40 to +85 degrees C. It is supplied in a 116-pin QFN package which measures 13 x 7.0mm.

Diodes delivers semiconductor products to companies in the consumer electronics, computing, communications, industrial, and automotive markets. Its product portfolio includes discrete, analogue and mixed-signal products and packaging technology to meet customers’ needs. There are 31 sites around the world, including engineering, testing, manufacturing, and customer service.

http://www.Diodes.com

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Single-stage flyback controllers from Infineon shape up smart LED lighting

Three single-stage flyback LED controllers for constant output voltages have been introduced by Infineon, in anticipation of increased demand for dimmable and intelligent LED systems.

The ICL8800, ICL8810 and ICL8820 single-stage flyback LED controllers meet performance requirements for LED lighting applications, such as LED drivers and luminaires up to 125W, smart lighting and emergency luminaires. The ICs can also be used in adapters and chargers, flat TVs as well as PCs and monitors up to 125W.

The three IC versions offer benchmarking performance for power factor correction and total harmonic distortion at full load and low load conditions, says Infineon. They are optimised as secondary side regulated (SSR) constant voltage (CV) output flyback controllers and are also suitable for primary side regulation (PSR). Critical conduction mode (CCM) and quasi-resonant mode (QRM) with smart valley hopping ensure low EMI without compromising light quality, says the company.

ICL8800 is the basic model, ICL8810 has an integrated burst mode that allows a very low standby power consumption of less than 100mW and flicker-free deep dimming down to 0.1 per cent. This makes the ICL8810 suitable for smart lighting applications in connection with microcontrollers. The ICL8820 is additionally equipped with an integrated DC-input jitter function to improve EMI performance and supports the fulfilment of EMI requirements in DC operation. The ICL8820 model is claimed to ease EMI certification in the design of emergency lighting LED driver applications without additional circuitry.

The ICL88xx family offers an external start-up circuit control signal with a set of protection features, including a power limitation and secondary side over-voltage protection. The ICs require a minimum number of external components, claims Infineon.

The gate driver current enables designs up to 125W with MOSFETs. System performance and efficiency can be further optimised using Infineon’s CoolMOS P7 power MOSFETs.

All three single-stage flyback LED controller variants are available in PG-DSO-8 packages and are available for order now.

http://www.infineon.com

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Hand-held camera cube reference design brings AI to the edge

Artificial intelligence (AI) which was previously limited to expensive machines with large power budgets can now be embedded in space-constrained, power-powered edge devices. Maxim Integrated says its MAXREFDES178# camera cube executes low latency AI vision and hearing inferences on a coin cell power budget with reduced cost and size.

The MAXREFDES178# enables low power IoT devices to implement hearing and vision. It is based on the MAX78000 low power microcontroller with neural network accelerator for audio and video inferences. The system also contains the MAX32666 low power Bluetooth microcontroller and two MAX9867 audio codecs. The system is delivered in a compact form factor to show how AI applications, such as facial identification and keyword recognition, can be embedded in low power, cost sensitive applications such as wearables and IoT devices.

AI applications require intensive computations, which is usually performed in the cloud or in expensive, power-hungry processors: self driving cars is an example. Maxim says that its MAXREFDES178# camera cube demonstrates how AI can operate on a low power budget, enabling applications that are time- and safety-critical to run on even the smallest of batteries. The MAX78000’s AI accelerator slashes the power of AI inferences up to 1,000x for vision and hearing applications, compared to other embedded solutions, reports Maxim. The AI inferences running on the MAXREFDES178# also show dramatic latency improvements, running more than 100x faster than on an embedded microcontroller.

The compact form factor of the camera cube (1.6 x 1.7 x 1.5inch of 41 x 44 x 39mm) allows AI to be implemented in wearables and other space-constrained IoT applications. The MAX78000 is up to 50 per cent smaller than the next-smallest GPU-based processor, says Maxim, and does not require other components like memories or complex power supplies to implement cost-effective AI inferences.

The MAXREFDES178# and the MAX78000 is available now, together with the MAX32666GWPBT+T RF microcontroller and the MAX9867EWV+T stereo codec   at Maxim Integrated’s website and authorised distributors.

http://www.maximintegrated.com

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