This blog post was originally published at Expedera’s website. It is reprinted here with the permission of Expedera. There is a lot more to understanding the capabilities of an AI engine than TOPS per watt. A rather arbitrary measure of the number of operations of an engine per unit of power, this metric completely misses […]
Measuring NPU Performance Read More +
This blog post was originally published at e-con Systems’ website. It is reprinted here with the permission of e-con Systems. AMRs (Autonomous Mobile Robots), smart signages, barcode scanning devices, surveillance systems, industrial handhelds, etc., are changing how businesses operate and connect with people. And embedded vision cameras play a vital role in enabling these devices
What is a UVC Camera, and What are the Different Types of UVC Cameras? Read More +
This blog post was originally published at Embedded.com on behalf of MegaChips. It is reprinted here with the permission of Embedded.com and MegaChips. As the need for artificial intelligence grows more common and technology needs become more sophisticated, companies looking to adopt edge AI into their products often find it to be a difficult challenge.
Implementing Edge AI: Look Before You Leap Read More +
On-device intelligence provides important benefits. This blog post was originally published at Qualcomm’s website. It is reprinted here with the permission of Qualcomm. Our latest AI research to personalize and adapt models while keeping data private One size doesn’t fit all. The need for intelligent, personalized experiences powered by AI is ever-growing. Our devices are
Enabling On-device Learning at Scale Read More +
This blog post was originally published at Tryolabs’ website. It is reprinted here with the permission of Tryolabs. At Tryolabs, we are passionate about building computer vision solutions that have real-world impact. Very often, this means integrating them to run on edge devices. In our journey to master AI on the edge, we have developed
Detecting Safety Helmets in Real-time Read More +
This blog post was originally published at e-con Systems’ website. It is reprinted here with the permission of e-con Systems. Time-of-Flight (ToF) cameras are powerful embedded vision solutions that provide real-time depth measurement – predominantly for applications that require autonomous and guided navigation. As you may know, ToF sensors use the light illumination technique where
What is Multipath Interference, and How Can You Minimize It In Time-of-flight Cameras? Read More +
This blog post was originally published at Syntiant’s website. It is reprinted here with the permission of Syntiant. In our last blog post, we gave insight for modelers into the vital performance statistics of edge silicon. In this blog post, we will show how modelers can leverage the true power and throughput performance of edge
How Neural Architectures Leverage Duty Cycling for Massive Efficiencies Read More +
This blog post was originally published at Qualcomm’s website. It is reprinted here with the permission of Qualcomm. To run neural networks efficiently at the edge on mobile, IoT, and other embedded devices, developers strive to optimize their machine learning (ML) models’ size and complexity while taking advantage of hardware acceleration for inference. For these
Neural Network Optimization with AIMET Read More +
This blog post was originally published at Lanner Electronics’ website. It is reprinted here with the permission of Lanner Electronics. In dense urban environments where traffic flow is heavy, keeping up with traffic control and maintaining road safety at intersections with the heaviest traffic is often tricky as vehicles and pedestrians’ behaviors are erratic and
The LEC-2290: An Edge AI Appliance for Traffic Infraction Prevention Read More +
This blog post was originally published at Syntiant’s website. It is reprinted here with the permission of Syntiant. Academic machine learning requires extensive toolsets for model training and evaluation, but the vast majority of academic work is more grounded in model capacity than looking at the energy cost of deploying those models. This puts modelers
Modeling for the Edge: How Neural Network Modelers Should Evaluate Edge Compute Power Read More +
Here you’ll find a wealth of practical technical insights and expert advice to help you bring AI and visual intelligence into your products without flying blind.
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