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What is computer vision?

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If I asked you to name the objects in the picture below, you would probably come up with a list of words such as "tablecloth, basket, grass, boy, girl, man, woman, orange juice bottle, tomatoes, lettuce, disposable plates…" without thinking twice. Now, if I told you to describe the picture below, you would probably say, "It's the picture of a family picnic" again without giving it a second thought. Those are two very easy tasks that any person with below-average intelligence and above the age of six or seven could accomplish. However, in the background, a very complicated process takes place. The human vision is a very intricate piece of organic technology that involves our eyes and visual cortex, but also takes into account our mental models of objects, our abstract understanding of concepts and our personal experiences through billions and trillions of interactions we've made with the world in our lives.


Why Biometric Security is the Future

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With nearly eight billion people on the planet -- and more than half of them on internet -- verifying who's who is one of the great technological challenges of our time. To meet this challenge, Biometric security is rising to the occasion, buoyed by technological advancements and user-friendly experiences. Modern biometrics can seem like science fiction, but the concept is far from new. Sir Francis Galton, cousin of the famous Charles Darwin, used an analysis of over 8,000 fingerprint samples to publish what would become the first fingerprint classification system in history. Building on the work of Sir Francis Galton, the Metropolitan Police of London used shapes like whorls and loops identify individuals based on fingerprint patterns at the beginning of the 20th century.


Chinese firm's facial recognition could ID you under a mask Digital Trends

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Let's say you live in a country where there's been reports of massive outbreaks of a highly contagious viral infection. Hypothetically, let's call this infection "coronavirus." To avoid spreading this "coronavirus," many people have taken to wearing medical face masks when going about their everyday life. These masks don't do much, medically speaking, but it's considered the polite thing to do. Now, let's also say that the government there is notorious for widespread and unregulated use of facial-recognition technology as a way to both fight crime and to identify and silence political dissidents.


YouTuber invents robotic basketball hoop with facial recognition to ensure people never miss

The Independent - Tech

Engineer and YouTuber Shane Wighton has made a basketball hoop that uses a Microsoft Kinect and facial recognition in order to build a basketball hoop that means the shooter never misses. On the YouTube channel Stuff Made Here, Wighton explains that the backboard is tracking the information in the room, including the ball and its trajectory. With that information, the backboard can calculate where it needs to move in order to ensure the ball gets into the hoop. Since there are only 600 milliseconds (a thousandth of a second) between when the ball is thrown and when it hits the backboard, the calculations need to be made in an incredibly short amount of time. Therefore, Wighton said, when designing the board he had to prioritise fast movement.


What Is Facial Recognition And How Is It Used?

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Facial recognition technology has dominated discussions in technology circles for some time now. Faced with increased surveillance in public spaces, it has become imperative for stakeholders to have some input on future deployments of these novel technologies. More importantly, the general public should have some degree of understanding of facial recognition and how it's being used today. Facial recognition is a term used to refer to technologies used to analyze and recognize faces from video recordings and still images. Advancements in image processing and AI have enabled today's computer to read even the subtlest details in the human face like eyelashes to differentiate people.


ARTIFICIAL INTELLIGENCE DANGERS TO HUMANITY

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China and Big Tech threaten all the worlds people with a Quantum AI Digital Brain on the coming 5G and 6G networks that can form an AI system beyond the control of human beings. "Artificial Intelligence Dangers to Humanity" goes deep into the inter-connections between AI, U.S, China, Big Tech and the worlds use of Facial Recognition, Bio-Metrics, Drones, Smart Phones, Smart Cities, IoT, VR, Mixed Reality, 5G, Robotics, Cybernetics, & Bio-Digital Social Programming. The book is sourced from a 10,000 page report converted to just over 200 pages with pictures and hidden inner meanings. We will cover present, emerging and future threats of Artificial Intelligence with Big Tech, including technology that can be used for assassination or to control humanities ability to have free formed thoughts without being formed by AI Bio-Digital Social Programming. The book will cover Cyborgs, Super Intelligence and how it can form, and in what ways it can travel undetected through The AI Global Network as it connects with the internet and the Human Bio-Digital Network.


How well can algorithms recognize your masked face?

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Facial-recognition algorithms from Los Angeles startup TrueFace are good enough that the US Air Force uses them to speed security checks at base entrances. But CEO Shaun Moore says he's facing a new question: How good is TrueFace's technology when people are wearing face masks? "It's something we don't know yet because it's not been deployed in that environment," Moore says. His engineers are testing their technology on masked faces and are hurriedly gathering images of masked faces to tune their machine-learning algorithms for pandemic times. Facial recognition has become more widespread and accurate in recent years, as an artificial intelligence technology called deep learning made computers much better at interpreting images.


Computer Vision: An overview about the field of computer vision

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Computer vision is a field in computer science that falls under the umbrella of artificial intelligence (AI). Computer vision (CV) software developers strive to give computers the ability to process images in much the same way that humans do. They expect the computer will be able to identify objects, to make appropriate decisions based on what it "sees," and then to produce relevant outputs. Today, facial recognition software, autonomous vehicles, certain forms of surveillance, and gesture recognition are just a few examples of CV systems at work. Why is computer vision so complicated? Every parent can recall their child going through phases when "what's that?" became a recurring question.


How Well Can Algorithms Recognize Your Masked Face?

WIRED

Facial-recognition algorithms from Los Angeles startup TrueFace are good enough that the US Air Force uses them to speed security checks at base entrances. But CEO Shaun Moore says he's facing a new question: How good is TrueFace's technology when people are wearing face masks? "It's something we don't know yet because it's not been deployed in that environment," Moore says. His engineers are testing their technology on masked faces and are hurriedly gathering images of masked faces to tune their machine-learning algorithms for pandemic times. Facial recognition has become more widespread and accurate in recent years, as an artificial intelligence technology called deep learning made computers much better at interpreting images.


5 Papers on Face Recognition Every Data Scientist Should Read

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Face recognition, or facial recognition, is one of the largest areas of research within computer vision. We can now use face recognition to unlock our mobile phones, verify identification at security gates, and in some countries, make purchases. With the ability to make numerous processes more efficient, many companies invest into the research and development of facial recognition technology. This article will highlight some of that research and introduce five machine learning papers on face recognition. With a multitude of real-world applications, face recognition technology is becoming more and more prominent.