Edge AI and Vision Alliance

LETTER FROM THE EDITOR Dear Colleague, You probably won’t be surprised that 84% of vision-based product developers are using DNNs. But did you know that 80+% are using non-neural network vision or imaging algorithms? Those are just two findings from last year’s Computer Vision and Perceptual AI Developer Survey. The Edge AI and Vision Alliance […]

SOFTWARE TOOLSETS Visual Anomaly Detection with FOMO-AD Virtually all computer vision machine learning models involve classification—for example, “how many humans are in the frame?” To train such a model, you need examples of every class of object the model is intended to detect. But what happens when a new type of object appears? Ask a

LOW-POWER SENSING AND PROCESSING Battery-powered Edge AI Sensing: A Case Study Implementing Low-power, Always-on Capability The trend of pushing AI/ML capabilities to the edge brings design challenges around the need to combine high-performance computing (for AI/ML algorithms) with low power consumption (to enable battery-powered sensing systems). Designers are often faced with a choice between using

DEVELOPMENT TOOL ADVANCEMENTS Deploy Your Embedded Vision Solution on Any Processor Vision-based product developers have a vast array of processors to choose from. Unfortunately, each processor has its own unique tool chain. This makes it difficult for developers to evaluate processor options and target different processors for different product needs. Fortunately, there’s Edge Impulse Studio—a

VISION PROCESSING AND ACCELERATION M1 NPU Delivers Flexibility, Accuracy, Efficiency and Performance For a growing range of applications, deploying AI in the real world means running various models at the edge. Fortunately, powerful edge processors are increasingly capable of handling demanding AI workloads. But performance alone is not sufficient. To meet the needs of real-world

IMPROVING VISION PRODUCT DEVELOPMENT Five Things You Might Overlook on Your Next Vision-enabled Product Design When you think about building a vision-enabled product, you probably think about things like: Which processor am I going to use? What neural network will it run? Where will I get the training data? These are important questions that need

OPEN SOURCE-BASED DEVELOPMENT TECHNIQUES Using Kubernetes to Speed Development and Deployment of Edge Computer Vision Applications In this 2022 Embedded Vision Summit presentation, Rakshit Agrawal, Vice President of Research and Development at Camio, presents real-world deployments of computer vision solutions using Kubernetes and shows how containerization enables continuous AI updates on a massive scale at

EMBEDDED VISION MARKET TRENDS AND PROCESSING SOLUTIONS Big Trends in Computer Vision: Health and Safety, Retail and Consumer Electronics Over the last few years computer vision technology has penetrated dozens of markets. The value of the computer vision market when this presentation was delivered at the 2022 Embedded Vision Summit was predicted to hit $48B