The Power of Memory in Camera Monitor Systems


According to the World Health Organization, approximately 1.19 million people die each year as a result of road traffic crashes. The challenge automakers have is deciding what types of cameras or sensors to implement to help prevent accidents, and making sure they meet various regulations. Camera monitoring systems or (CMS) represent a significant milestone in the ongoing evolution of automo... » read more

How To Build Computer Vision Solutions


Computer vision devices that can ‘see’ and act on visual information are bringing new efficiencies and functionalities to IoT. But with new opportunities come complexities. The specific features and functionality of smart vision use cases vary widely. Creating a system that catches defects on an assembly line requires different imaging, machine learning, and workloads compared to one ... » read more

See The Future of IoT: Planning For Success With Smart Vision


Computer vision devices that can ‘see’ and act on visual information are bringing new efficiencies and functionalities to IoT. But with new opportunities come complexities. The specific features and functionality of smart vision use cases vary widely. Creating a system that catches defects on an assembly line requires different imaging, machine learning, and workloads compared to one ... » read more

Vision Transformers Change The AI Acceleration Rules


Transformers were first introduced by the team at Google Brain in 2017 in their paper, "Attention is All You Need". Since their introduction, transformers have inspired a flurry of investment and research which have produced some of the most impactful model architectures and AI products to-date, including ChatGPT which is an acronym for Chat Generative Pre-trained Transformer. Transformers a... » read more

(Vision) Transformers: Rise Of The Chimera


It’s 2023 and transformers are having a moment. No, I’m not talking about the latest installment of the Transformers movie franchise, "Transformers: Rise of the Beasts"; I’m talking about the deep learning model architecture class, transformers, that is fueling anticipation, excitement, fear, and investment in AI. Transformers are not so new in the world of AI anymore; they were first ... » read more

Object Detection CNN Suitable For Edge Processors With Limited Memory


A technical paper titled “TinyissimoYOLO: A Quantized, Low-Memory Footprint, TinyML Object Detection Network for Low Power Microcontrollers” was published by researchers at ETH Zurich. Abstract: "This paper introduces a highly flexible, quantized, memory-efficient, and ultra-lightweight object detection network, called TinyissimoYOLO. It aims to enable object detection on microcontrol... » read more

Computational Imaging Craves System-Level Design And Simulation Tools To Leverage Disruptive AI In Embedded Vision


Image quality now relies more than ever on high computing power tied to miniaturized optics and sensors, rather than on standalone and bulky but aberration-free optics. This new trend is called computational imaging and can be used either for computational photography or for computer vision. Read this white paper to learn about market trends and promising system co-design and co-optimization ap... » read more

Machine Vision Plus AI/ML Adds Vast New Opportunities


Traditional technology companies and startups are racing to combine machine vision with AI/ML, enabling it to "see" far more than just pixel data from sensors, and opening up new opportunities across a wide swath of applications. In recent years, startups have been able to raise billions of dollars as new MV ideas come to light in markets ranging from transportation and manufacturing to heal... » read more

Performance Of Analog In-Memory Computing On Imaging Problems


A technical paper titled "Accelerating AI Using Next-Generation Hardware: Possibilities and Challenges With Analog In-Memory Computing" was published by researchers at Lund University and Ericsson Research. Abstract "Future generations of computing systems need to continue increasing processing speed and energy efficiency in order to meet the growing workload requirements under stringent en... » read more

Issues And Challenges In Super-Resolution Object Detection And Recognition


If you want high performance AI inference, such as Super-Resolution Object Detection and Recognition, in your SoC the challenge is to find a solution that can meet your needs and constraints. You need inference IP that can run the model you want at high accuracy. You need inference IP that can run the model at the frame rate you want: higher frame rate = lower latency, more time for dec... » read more

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