Image Recognition Statistics


Steve Goldstein
Steve Goldstein
Business Formation Expert
Steve Goldstein runs LLCBuddy, helping entrepreneurs set up their LLCs easily. He offers clear guides, articles, and FAQs to simplify the process. His team keeps everything accurate and current, focusing on state rules, registered agents, and compliance. Steve’s passion for helping businesses grow makes LLCBuddy a go-to resource for starting and managing an LLC.

All Posts by Steve Goldstein →
Business Formation Expert  |   Fact Checked by Editorial Staff
Last updated: 
LLCBuddy™ offers informative content for educational purposes only, not as a substitute for professional legal or tax advice. We may earn commissions if you use the services we recommend on this site.
At LLCBuddy, we don't just offer information; we provide a curated experience backed by extensive research and expertise. Led by Steve Goldstein, a seasoned expert in the LLC formation sector, our platform is built on years of hands-on experience and a deep understanding of the nuances involved in establishing and running an LLC. We've navigated the intricacies of the industry, sifted through the complexities, and packaged our knowledge into a comprehensive, user-friendly guide. Our commitment is to empower you with reliable, up-to-date, and actionable insights, ensuring you make informed decisions. With LLCBuddy, you're not just getting a tutorial; you're gaining a trustworthy partner for your entrepreneurial journey.

Image Recognition Statistics 2023: Facts about Image Recognition outlines the context of what’s happening in the tech world.

LLCBuddy editorial team did hours of research, collected all important statistics on Image Recognition, and shared those on this page. Our editorial team proofread these to make the data as accurate as possible. We believe you don’t need to check any other resources on the web for the same. You should get everything here only 🙂

Are you planning to form an LLC? Maybe for educational purposes, business research, or personal curiosity, whatever the reason is – it’s always a good idea to gather more information about tech topics like this.

How much of an impact will Image Recognition Statistics have on your day-to-day? or the day-to-day of your LLC Business? How much does it matter directly or indirectly? You should get answers to all your questions here.

Please read the page carefully and don’t miss any words.

Top Image Recognition Statistics 2023

☰ Use “CTRL+F” to quickly find statistics. There are total 47 Image Recognition Statistics on this page 🙂

Image Recognition “Latest” Statistics

  • According to Smith (2020), 56% of Americans believe that law enforcement will appropriately screen for dangers in public spaces using face recognition technology.[1]
  • Customer satisfaction will be improved, according to 62% of respondents, if face recognition technology is used to identify hotel visitors, according to Oracle Hospitality.[1]
  • In the United States, 86% of individuals are acquainted with face recognition technology, while 13% are completely ignorant about it.[1]
  • Only 32% of customers, according to a research by Capers (2020), are comfortable with private enterprises using face recognition technology.[1]
  • 59.4% of Americana people agree that if face recognition technology has a 100% accuracy rate, police should be permitted to use it to find offenders.[1]
  • 16.1% of Americans strongly agree that the use of surveillance cameras should be regulated by the government.[1]
  • 41% claimed that they are more inclined to stay at hotels equipped with automatic face recognition technology.[1]
  • According to Statista, 49% of people think that shops should use face recognition technology to prevent stealing.[1]
  • Gender identification is 99% accurate on photos of white men, but a facial recognition error rate of nearly 35% occurs when identifying the gender on photos of darker-skinned women.[1]
  • The face recognition market is anticipated to expand at a compound annual growth rate of 14.5% between 2020 and 2027. (Grand View Research, 2020).[1]
  • In the U.S, 30% of individuals agree that using face recognition technology to track employee attendance is appropriate.[1]
  • 74% of U.S respondents think face recognition technology works well for properly identifying people.[1]
  • In Spain, a study by CaixaBank shows that 70% of users would be willing to use facial recognition instead of PIN when withdrawing money from ATMs.[1]
  • According to Castro & McLaughlin (2019), 55% of respondents oppose strong regulation of face recognition, particularly when it is used to protect the public.[1]
  • Only 16% of Americans believe that the use of face recognition technology should be carefully limited by the government.[1]
  • According to Oracle Hospitality, 74% of hotel owners believe that by 2025, everyone will be using biometrics to identify hotel workers.[1]
  • By using face recognition technology in retail settings, violent events may be reduced by 91%.[1]
  • Regarding residential building owners using face recognition to improve security 34% of American people disagree, while 30% believe it is an appropriate measure.[1]
  • When it comes to ethnicity, White adult Americans (64%) agree that law enforcement can be trusted with facial recognition technology than Black (47%) and Hispanic (55%) respondents.[1]
  • The best performing face recognition system was able to achieve an identification rate of 96% despite the fact that system performance varied.[1]
  • About 30% of US citizens believe that using face recognition technology to track employee attendance is appropriate.[2]
  • 36% of americans believe that technology firms will appropriately utilize facial recognition.[2]
  • The majority of US adults—roughly 73% —believe face recognition can identify persons fairly accurately.[2]
  • In response to an ongoing terrorist incident, over 76% of Americans think law enforcement should employ face recognition technology to identify terrorists.[2]
  • 59% support the use of FRT by law enforcement to evaluate security hazards in public areas.[2]
  • 76% are in favor of mandating that law enforcement undergo training in FRT use and risk awareness.[2]
  • The majority of Americans—roughly 76% —support utilizing FRT in schools to detect known child predators.[2]
  • Facebook DeepFace has a 97% accuracy rate for determining if two faces in photographs belong to the same individual.[2]
  • Less than 40% of people find it acceptable for FRT to be used for tracking who enters or leaves residential buildings, monitoring employee attendance (30%), or seeing how people respond to advertising displays in real-time (15%).[2]
  • 56% of Americans believe that law enforcement will appropriately utilize face recognition technology.[2]
  • For tracking, monitoring, or reducing COVID-19 transmission, more than 40% of nations utilize face recognition.[2]
  • The 3D sector led the facial recognition market in 2020, making up 36% of the global revenue share, followed by the retail and e-commerce segment at 21%.[2]
  • From 2021 to 2028, the face recognition market, which was valued at $3.8 billion in 2020, is anticipated to expand at a compound annual growth rate of 15.4% .[2]
  • One indicative set of algorithms tested under the FRVT had an average miss rate of 4.7% on photos “from the wild” when matching without any confidence threshold.[3]
  • Leading algorithms exhibited accuracy ranges between 36% and 87% when detecting people passing through a sports event.[3]
  • The top algorithm had an accuracy rate of 94.4% when utilizing video of people going via boarding gates in a reasonably controlled environment.[3]
  • In around 30% of situations, the algorithm correctly recognized the person, but did so with less than 99% confidence, and as a result, claimed that it had no matches.[3]
  • Using the best practices as tools now download complex architectural systems can estimate an object’s face in a picture with 95% accuracy, outperforming humans’ 94% accuracy, according to einfochips.com.[4]
  • The market for computer-based vision has grown considerably. It is currently valued at $11.94 billion and is likely to reach $17.38 billion by 2023, at a CAGR of 7.80% between 2018 and 2023.[4]
  • By 2021, facial recognition will be in use at the top 20 U.S. airports for 100% of international passengers, including American citizens.[5]
  • 42.6% of respondents support using face recognition technology to increase boarding efficiency and security, according to reservations.com.[5]
  • Only one in three Americans (32.5%) disagree with the government using facial recognition technology at airports to improve security and boarding speed, according to a new survey from travel search engine Reservations.com.[5]
  • According to a report released in June 2019, the worldwide face recognition industry will produce $7 billion in sales by 2024, with a CAGR of 1.6% from 2019 to 2024.[6]
  • Academia in comparison to human face recognition scores of 97.53%, the 2014 Gaussian face algorithm created by academics at the Chinese University of Hong Kong attained facial identification ratings of 98.52%.[6]
  • According to a recent NIST study, significant improvements in recognition accuracy have been accomplished over the last five years, surpassing those made between 2010 and 2013.[6]
  • According to the Boston Globe, on June 27, 2019, the Somerville City council in Massachusetts’s decided to outlaw face recognition technology, becoming the second city to do so.[6]
  • According to Yahoo, the face recognition payment system will be implemented in 3,000 businesses by the end of the year.[6]

Also Read

How Useful is Image Recognition

Image recognition, also known as computer vision, has proven itself to be a valuable tool in a multitude of fields. In healthcare, it can aid doctors in diagnosing diseases and identifying abnormalities in medical images. In retail, it enables businesses to track inventory levels and manage shipments more effectively. In security, it helps to monitor and identify individuals in real-time, increasing safety measures in public spaces.

One of the most significant benefits of image recognition technology is its ability to automate tasks that are time-consuming or difficult for humans to perform. For example, in the manufacturing industry, image recognition can be used to inspect products for defects, speeding up the quality control process and reducing the margin of error. In agriculture, it can help farmers monitor crops and animals, ensuring they receive proper care and attention.

Furthermore, image recognition technology has the potential to revolutionize the way we interact with our environment. For instance, augmented reality applications use image recognition to overlay digital information onto real-world objects, creating immersive experiences for users. This technology also has implications for accessibility, as it can assist individuals with visual impairments in their daily lives.

However, while image recognition technology has many advantages, it also raises concerns about privacy, security, and ethical implications. The widespread use of facial recognition technology, for example, has sparked debates about surveillance and data privacy. There are also issues with bias and discrimination in algorithms, as they may have inherent flaws that result in unfair treatment of certain groups of people.

Ultimately, the usefulness of image recognition technology comes down to how it is implemented and regulated. It is essential for businesses and policymakers to prioritize ethical considerations and protect individuals’ rights and privacy. Transparency and accountability are crucial in ensuring that image recognition technology is used responsibly and ethically.

In conclusion, image recognition technology has the potential to revolutionize industries and improve our daily lives in numerous ways. However, it is crucial to be aware of its limitations and potential drawbacks, and to address issues such as privacy, security, and bias. With the right regulations and safeguards in place, image recognition can continue to be a valuable tool for innovation and progress in the modern world.

Reference

  1. financesonline – https://financesonline.com/facial-recognition-statistics/
  2. passport-photo – https://passport-photo.online/blog/facial-recognition-statistics/
  3. csis – https://www.csis.org/blogs/technology-policy-blog/how-accurate-are-facial-recognition-systems-%E2%80%93-and-why-does-it-matter
  4. einfochips – https://www.einfochips.com/blog/understanding-image-recognition-and-its-uses/
  5. reservations – https://www.reservations.com/blog/resources/facial-recognition-airports-survey/
  6. thalesgroup – https://www.thalesgroup.com/en/markets/digital-identity-and-security/government/biometrics/facial-recognition

Leave a Comment