Review of Automatic EM Image Algorithms for Semiconductor Defect Inspection (KU Leuven, Imec)


A new technical paper titled "Electron Microscopy-based Automatic Defect Inspection for Semiconductor Manufacturing: A Systematic Review" was published by researchers at KU Leuven and imec. Abstract: "In this review, automatic defect inspection algorithms that analyze Electron Microscope (EM) images of Semiconductor Manufacturing (SM) products are identified, categorized, and discussed. Thi... » read more

Fundamental Issues In Computer Vision Still Unresolved


Given computer vision’s place as the cornerstone of an increasing number of applications from ADAS to medical diagnosis and robotics, it is critical that its weak points be mitigated, such as the ability to identify corner cases or if algorithms are trained on shallow datasets. While well-known bloopers are often the result of human decisions, there are also fundamental technical issues that ... » read more

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

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