The recent surveys, studies, forecasts and other quantitative assessments of the health and progress of AI provided new numbers regarding business leaders' assessment of China as a global AI leader, the current worldwide ranking of China's AI-related entrepreneurial and research activities, plans for AI adoption by U.S. enterprises and expectations regarding its impact on jobs, and the use of AI in face recognition, physical security monitoring, cashierless retail, categorizing open-ended survey responses, and detecting plant diseases and atrial fibrillation. A doctor examines a magnetic resonance image on a computer screen during the CHAIN Cup at the China National Convention Center in Beijing, June 30, 2018. A computer running artificial intelligence software defeated two teams of human doctors in accurately recognizing maladies in magnetic resonance images in a contest that was billed as the world's first competition in neuroimaging between AI and human experts. The U.S. Department of Homeland Security estimates face recognition will scrutinize 97% of outbound airline passengers by 2023 [The Economist] More than 4.5 million websites use reCAPTCHA and the system collects hundreds of millions of daily solves or more than 100 person-years of labor every day; Google/reCAPTCHA has extracted to date over $7 billion of free labor [hcaptcha] The Bureau of Labor Statistics' injury and illness database is built upon text-based descriptions of work-related injuries and illnesses it receives from workplaces across the country each year; categorizing the description into actionable data used to be done manually, but this year, the BLS has done 80% of that automatically using deep neural networks [governmentCIO] The AI market worldwide is estimated to grow by $75.54 billion from 2019 to 2023 [Technavio] The AI market worldwide is estimated to reach $202.57 Data is eating the world quote of the week: "The market for data labeling passed $500 million in 2018 and it will reach $1.2 billion by 2023, according to the research firm Cognilytica. This kind of work, the study showed, accounted for 80 percent of the time spent building A.I. technology"--The New York Times AI is "mimicking the brain" quote of the week: "Computer vision… is nothing like the human sort"--The Economist Robots are eating the world quote of the week: "A human can certainly move a part faster than a cobot [collaborative robot]. However, it does not take coffee breaks and continues to work for several hours after we have already gone home"--Pekka Myller, Ket-Met Robots are eating the world quote of the 19th century: "[A Linotype] could work like six men and do everything but drink, swear, and go out on strike"--Mark Twain
ABSTRACT Considering the existence of very large amount of available data repositories and reach to the very advanced system of hardware, systems meant for facial identification have evolved enormously over the past few decades. Sketch recognitio n is one of the most important areas that have evolved as an integral component adopted by the agencies of law administration in curren t trends of forensic science. Matching of derived sketches to photo images of face is also a difficult assignment as the considered sketches are produced upon the verbal explanation depicted by the eye witness of the crime scene and may have scarcity of se nsitive elements that exist in the photograph as one can accurately depict due to the natural human error. Substantial amount of the novel research work carried out in this area up late used recognition system through traditional extraction and classificat ion models . But very recently, few researches work focused on using deep learning techniques to take an advantage of learning models for the feature extraction and classification to rule out potential domain challenges. The first part of this review paper basically focuses on deep learning techniques used in face recognition and matching which as improved the accuracy of face recognition technique with training of huge sets of data. This paper also includes a survey on different techniques used to match com posite sketches to human images which includes component - based representation approach, automatic composite sketch recognition technique etc. INTRODUCTION As per the researches carried out, a complete face recognition system includes two patterns of face detection and face recognition: 1) Structural similarity and 2) individual local differences of human faces. Therefore, it is required to extract the features of the face through the face detection process. The evolution of face recognition is due to its technical challenges and huge potential application in video surveillance, identity authorization, multimedia applications, home and office security, law enforcement and different human - computer interaction activities. Facial recognition technology (FRT) is one of the most controversial new tools. It was first devel oped in the 1960s.
In the past few years, there's been a dramatic rise in the adoption of face recognition, detection, and analysis technology. You're probably most familiar with recognition systems, like Facebook's photo-tagging recommender and Apple's FaceID, which can identify specific individuals. Detection systems, on the other hand, determine whether a face is present at all; and analysis systems try to identify aspects like gender and race. All of these systems are now being used for a variety of purposes, from hiring and retail to security and surveillance. Many people believe that such systems are both highly accurate and impartial.
As of today, lots of companies state to assist security firms, the army, in addition to consumers prevent crime and defend their private, homes, and buildings belongings. This particular article intends to offer business leaders in the security space with a concept of what they are able to presently expect from Ai in the business of theirs. We wish this report allows company leaders in security to garner insights they are able to confidently relay to the executive teams of theirs so they are able to make educated choices when thinking about AI adoption. At the minimum, this article intends to serve as a technique of decreasing the time industry leaders in physical security spend researching AI businesses with whom they might (or might not) be keen on working. Evolv Technology claims to offer a physical security system that consists of the Evolve Edgepersonnel threat screening machine that works with the Evolv Pinpoint automated facial recognition application.
Dubai: Thousands of CCTV cameras of various Dubai government agencies will now provide live feed to a central command centre, officials said. Under a new Artificial Intelligence (AI) network, security cameras across will relay live images of security breaches live to the central command centre, Dubai Police said. The cameras will monitor criminal behaviour in three sectors -- tourism, traffic and bricks and mortar facilities. The network, said the police, is being phased in via different stages to meet the Dubai 2021 Vision requirements of a smart city. Announcing the programme, Major-General Khalil Ebrahim Al Mansouri, Assistant Commander-in-Chief for Criminal Investigation Affairs, said the new project called'Oyoon' (eyes) will tackle crimes in the city and help reduce traffic accident deaths and congestion.