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== 노트 ==
 
== 노트 ==
  
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* Ovomatch applies facial recognition to assisted reproduction treatments.<ref name="ref_eb9a">[https://ovoclinic.net/facial-recognition-system/?lang=en Facial Recognition System]</ref>
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===위키데이터===
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* The statistical analysis underpinning facial recognition and other similar technology is often referred to as a “black box”.<ref name="ref_c10c">[https://edri.org/our-work/facial-recognition-and-fundamental-rights-101/ Facial recognition and fundamental rights 101]</ref>
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* ID :  [https://www.wikidata.org/wiki/Q1192553 Q1192553]
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* But what if we continue to be seduced by the allure of facial recognition?<ref name="ref_c10c" />
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* The essay reviews some of the most advanced computational approaches for face recognition defined till date.<ref name="ref_289a">[https://link.springer.com/10.1007%2F978-0-387-73003-5_84 Face Recognition, Overview]</ref>
+
===말뭉치===
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* Private industry and government are developing policies, principles and best practices for the appropriate use of facial recognition.<ref name="ref_8d7e">[https://www.ncsl.org/research/telecommunications-and-information-technology/facial-recognition-gaining-measured-acceptance-magazine2020.aspx Facial Recognition Gaining Measured Acceptance]</ref>
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# Telpo Android OS face recognition machines have good compatibility and extensibility.<ref name="ref_a25c874f">[https://www.telpo.com.cn/face-recognition-machine/ Face Recognition Machine Manufacturer]</ref>
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* No federal laws address commercial uses of facial recognition, but three states have privacy protections in place for consumers.<ref name="ref_8d7e" />
+
# Further, because it is the first step in a broader face recognition system, face detection must be robust.<ref name="ref_c235b1e0">[https://machinelearningmastery.com/introduction-to-deep-learning-for-face-recognition/ A Gentle Introduction to Deep Learning for Face Recognition]</ref>
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* This year, Washington state enacted one of the most comprehensive laws governing the use of facial recognition by government.<ref name="ref_8d7e" />
+
# A face recognition system is expected to identify faces present in images and videos automatically.<ref name="ref_c235b1e0" />
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* He had favored a one-year moratorium on the use of facial recognition, due to concerns about bias in the technology.<ref name="ref_8d7e" />
+
# The holistic approaches dominated the face recognition community in the 1990s.<ref name="ref_c235b1e0" />
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* Facial recognition systems are computer-based security systems that are able to automatically detect and identify human faces.<ref name="ref_973b">[https://epic.org/privacy/facerecognition/ Facial Recognition]</ref>
+
# There are perhaps four milestone systems on deep learning for face recognition that drove these innovations; they are: DeepFace, the DeepID series of systems, VGGFace, and FaceNet.<ref name="ref_c235b1e0" />
−
* Recently, the focus on facial recognition systems has shifted to its use as a way to secure borders.<ref name="ref_973b" />
+
# Considering roughly presented elements above of the complex process of face recognition, a number of limitations and imperfections can be seen.<ref name="ref_a471f1e6">[https://www.intechopen.com/books/face-recognition-semisupervised-classification-subspace-projection-and-evaluation-methods/face-recognition-issues-methods-and-alternative-applications Face Recognition: Issues, Methods and Alternative Applications]</ref>
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* Most people have seen facial recognition used in movies for decades (video), but it’s rarely depicted correctly.<ref name="ref_9396">[https://www.nytimes.com/wirecutter/blog/how-facial-recognition-works/ Facial Recognition Is Everywhere. Here’s What We Can Do About It.]</ref>
+
# It is the fact that face recognition systems are still not very robust regarding to deviations from ideal face image.<ref name="ref_a471f1e6" />
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* The detection phase of facial recognition starts with an algorithm that learns what a face is.<ref name="ref_9396" />
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# Recent advances in automated face analysis, pattern recognition and machine learning have made it possible to develop automatic face recognition systems to address these applications.<ref name="ref_a471f1e6" />
−
* Facial recognition’s first dramatic shift to the public stage in the US also brought on its first big controversy.<ref name="ref_9396" />
+
# Being part of a biometric technology, automated face recognition has a plenty of desirable properties.<ref name="ref_a471f1e6" />
−
* In 2001, law enforcement officials used facial recognition on crowds at Super Bowl XXXV.<ref name="ref_9396" />
+
# Research on face recognition to reliably locate a face in an image that contains other objects gained traction in the early 1990s with the principle component analysis (PCA).<ref name="ref_194277d0">[https://en.wikipedia.org/wiki/Facial_recognition_system Facial recognition system]</ref>
−
* Facial recognition has improved dramatically in only a few years.<ref name="ref_dd9f">[https://www.csis.org/blogs/technology-policy-blog/how-accurate-are-facial-recognition-systems-%E2%80%93-and-why-does-it-matter How Accurate are Facial Recognition Systems – and Why Does It Matter?]</ref>
+
# LDA Fisherfaces became dominantly used in PCA feature based face recognition.<ref name="ref_194277d0" />
−
* In ideal conditions, facial recognition systems can have near-perfect accuracy.<ref name="ref_dd9f" />
+
# Some face recognition algorithms identify facial features by extracting landmarks, or features, from an image of the subject's face.<ref name="ref_194277d0" />
−
* In these cases, facial recognition is just a tool to speed human identification rather than being used for identification itself.<ref name="ref_dd9f" />
+
# Other algorithms normalize a gallery of face images and then compress the face data, only saving the data in the image that is useful for face recognition.<ref name="ref_194277d0" />
−
* Understanding the proper role of confidence intervals is essential when considering the way facial recognition is being deployed.<ref name="ref_dd9f" />
+
# Face recognition is a technology capable of identifying or verifying a subject through an image, video or any audiovisual element of his face.<ref name="ref_da028ff2">[https://www.electronicid.eu/en/blog/post/face-recognition/en Face Recognition: how it works and its safety]</ref>
−
* While facial recognition may seem futuristic, it’s currently being used in a variety of ways.<ref name="ref_4664">[https://www.pandasecurity.com/en/mediacenter/panda-security/facial-recognition-technology/ The Complete Guide to Facial Recognition Technology]</ref>
+
# The objective of face recognition is, from the incoming image, to find a series of data of the same face in a set of training images in a database.<ref name="ref_da028ff2" />
−
* Other apps use facial recognition for the purpose of protecting your data.<ref name="ref_4664" />
+
# Thanks to the use of artificial intelligence (AI) and machine learning technologies, face recognition systems can operate with the highest safety and reliability standards.<ref name="ref_da028ff2" />
−
* Even a secure password can’t protect your accounts and information from skilled hackers so people have turned to facial recognition.<ref name="ref_4664" />
+
# Face recognition uses focus on verification or authentication.<ref name="ref_da028ff2" />
−
* There are healthcare apps such as Face2Gene and software like DeepGestalt that use facial recognition to detect a genetic disorder.<ref name="ref_4664" />
+
# With the constant support of our dexterous crew of technocrats, we are fulfilling the varied requirements of clients by manufacturing and supplying optimum quality Face Recognition Machine.<ref name="ref_b0589a7c">[https://www.indiamart.com/proddetail/face-recognition-machine-4392933473.html Face Recognition Machine]</ref>
−
* Facial recognition systems are built on computer programs that analyze images of human faces for the purpose of identifying them.<ref name="ref_dbaf">[https://www.aclu.org/issues/privacy-technology/surveillance-technologies/face-recognition-technology Face Recognition Technology]</ref>
+
# We are actively engaged in offering high performance Face Recognition Machine, which is procured from certified vendors of the industry.<ref name="ref_b0589a7c" />
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* That’s because facial recognition has all kinds of commercial applications.<ref name="ref_3030">[https://us.norton.com/internetsecurity-iot-how-facial-recognition-software-works.html How does facial recognition work?]</ref>
+
# The offered face recognition machine is robustly designed by our reliable vendors in compliance with international quality standards.<ref name="ref_b0589a7c" />
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* Facial recognition is a way of recognizing a human face through technology.<ref name="ref_3030" />
+
# This face recognition machine is widely used in various corporate sectors, offices, etc.<ref name="ref_b0589a7c" />
−
* A facial recognition system uses biometrics to map facial features from a photograph or video.<ref name="ref_3030" />
+
# This article opens up what face recognition is from a technology perspective, and how deep learning increases its capacities.<ref name="ref_109071d8">[https://mobidev.biz/blog/custom-face-detection-recognition-software-development Face Recognition App Development Using Deep Learning]</ref>
−
* A lot of people and organizations use facial recognition — and in a lot of different places.<ref name="ref_3030" />
+
# Realizing the weaknesses of face recognition systems, data scientists went further.<ref name="ref_109071d8" />
−
* 93,95,128, Three-dimensional face recognition: In 2D image-based techniques, some features are lost owing to the 3D structure of the face.<ref name="ref_8bb6">[https://www.mdpi.com/1424-8220/20/2/342/htm Face Recognition Systems: A Survey]</ref>
+
# By applying traditional computer vision techniques and deep learning algorithms, they fine-tuned the face recognition system to prevent attacks and enhance accuracy.<ref name="ref_109071d8" />
−
* Information can also be shared between facial recognition systems by importing generic photo data in the JPEG format, etc.<ref name="ref_6ca1">[https://security.panasonic.com/products_technology/technologies/facial_recognition/ Facial Recognition｜Technologies｜Products & Technology｜Panasonic Security System]</ref>
+
# Deep learning is one of the most novel ways to improve face recognition technology.<ref name="ref_109071d8" />
−
* Face recognition is a method of identifying or verifying the identity of an individual using their face.<ref name="ref_4ec9">[https://www.eff.org/pages/face-recognition Face Recognition]</ref>
+
# Even though face recognition is promising, it does have some flaws.<ref name="ref_4b88c966">[https://shuftipro.com/blog/how-machine-learning-changed-facial-recognition-technology How machine learning changed facial recognition technology?]</ref>
−
* Additionally, face recognition has been used to target people engaging in protected speech.<ref name="ref_4ec9" />
+
# Simple face recognition systems could easily be spoofed by using paper-based images from the internet.<ref name="ref_4b88c966" />
−
* Law enforcement agencies are using face recognition more and more frequently in routine policing.<ref name="ref_4ec9" />
+
# Face recognition is only the beginning of implementing this method.<ref name="ref_ad127313">[https://towardsdatascience.com/how-to-build-a-face-detection-and-recognition-system-f5c2cdfbeb8c How to build a face detection and recognition system]</ref>
−
* Face recognition has been used in airports, at border crossings, and during events such as the Olympic Games.<ref name="ref_4ec9" />
+
# A classical 2D face recognition system operates on images or videos obtained from surveillance systems, commercial/private cameras, CCTV, or similar everyday hardware.<ref name="ref_ed29ec68">[https://www.mdpi.com/2079-9292/9/8/1188/htm Past, Present, and Future of Face Recognition: A Review]</ref>
−
* A video doorbell with facial recognition will tell you, provided you’ve uploaded a photo of the person’s face.<ref name="ref_1fa4">[https://www.theguardian.com/technology/2019/jul/29/what-is-facial-recognition-and-how-sinister-is-it What is facial recognition - and how sinister is it?]</ref>
+
# To sum up, all holistic methods are prevalent in the implementation of face recognition systems.<ref name="ref_ed29ec68" />
−
* There have been reports that Israel is using facial recognition for covert tracking of Palestinians deep inside the West Bank.<ref name="ref_1fa4" />
+
# It is generally known that in this perspective, the variations in lighting that contemplate face recognition present one of the significant challenges.<ref name="ref_ed29ec68" />
−
* It’s not the only way the police use facial recognition.<ref name="ref_1fa4" />
+
# Attention and fixations play a crucial function in human face recognition.<ref name="ref_ed29ec68" />
−
* Police trials have highlighted further shortcomings of facial recognition.<ref name="ref_1fa4" />
+
# In this paper we study the performance of the one-against-all (OAA) and one-against-one (OAO) ELM for classification in multi-label face recognition applications.<ref name="ref_3d7dd110">[https://www.sciencedirect.com/science/article/pii/S0925231211002578 Face recognition based on extreme learning machine]</ref>
−
* Being part of a biometric technology, automated face recognition has a plenty of desirable properties.<ref name="ref_f821">[https://www.intechopen.com/books/face-recognition-semisupervised-classification-subspace-projection-and-evaluation-methods/face-recognition-issues-methods-and-alternative-applications Face Recognition: Issues, Methods and Alternative Applications]</ref>
+
# Much like databases today, face recognition will be used for all sorts of things in many parts of societies, including many things that don’t today look like a face recognition use case.<ref name="ref_f74ad896">[https://www.ben-evans.com/benedictevans/2019/9/6/face-recognition Face recognition and AI ethics — Benedict Evans]</ref>
−
* Researchers, as well as civil-liberties advocates and legal scholars, are among those disturbed by facial recognition’s rise.<ref name="ref_bce5">[https://www.nature.com/articles/d41586-020-03188-2 Resisting the rise of facial recognition]</ref>
+
# We might be comfortable with our bank using face recognition as well.<ref name="ref_f74ad896" />
−
* The firm’s former head, Alexey Minin, said at the time that it was the world’s largest system of live facial recognition.<ref name="ref_bce5" />
+
# Part of the experience of databases, though, was that some things create discomfort only because they’re new and unfamiliar, and face recognition is the same.<ref name="ref_f74ad896" />
−
* In China, too, people have expressed discomfort with widespread use of facial recognition — by private firms, at least.<ref name="ref_bce5" />
+
# The cutting edge work is still limited to a relatively small number of companies and institutions, but ‘face recognition’ is now freely available to any software company to build with.<ref name="ref_f74ad896" />
−
* Automated facial recognition was pioneered in the 1960s.<ref name="ref_2ca8">[https://en.wikipedia.org/wiki/Facial_recognition_system Facial recognition system]</ref>
+
# Face recognition is a method for identifying an unknown person or authenticating the identity of a specific person from their face.<ref name="ref_af7d94ee">[https://www.infoworld.com/article/3573069/what-is-face-recognition-ai-for-big-brother.html What is face recognition? AI for Big Brother]</ref>
−
* LDA Fisherfaces became dominantly used in PCA feature based face recognition.<ref name="ref_2ca8" />
+
# Another approach to face recognition is to normalize and compress 2-D facial images, and to compare these with a database of similarly normalized and compressed images.<ref name="ref_af7d94ee" />
−
* To accomplish this computational task, facial recognition systems perform four steps.<ref name="ref_2ca8" />
+
# Three-dimensional face recognition uses 3-D sensors to capture the facial image, or reconstructs the 3-D image from three 2-D tracking cameras pointed at different angles.<ref name="ref_af7d94ee" />
−
* One advantage of 3D face recognition is that it is not affected by changes in lighting like other techniques.<ref name="ref_2ca8" />
+
# Adding skin texture analysis to 2-D or 3-D face recognition can improve the recognition accuracy by 20 to 25 percent, especially in the cases of look-alikes and twins.<ref name="ref_af7d94ee" />
−
* The solution utilizing live facial recognition performed exceptionally well at the rally.<ref name="ref_ea83">[https://www.thalesgroup.com/en/markets/digital-identity-and-security/government/biometrics/biometric-software/live-face-identification-system Facial recognition software]</ref>
+
# Built using dlib's state-of-the-art face recognition built with deep learning.<ref name="ref_01c00c06">[https://github.com/ageitgey/face_recognition ageitgey/face_recognition: The world's simplest facial recognition api for Python and the command line]</ref>
 +
# Face recognition can be done in parallel if you have a computer with multiple CPU cores.<ref name="ref_01c00c06" />
 +
# The face recognition model is trained on adults and does not work very well on children.<ref name="ref_01c00c06" />
 +
# MX RT106F crossover MCU, enabling developers to quickly and easily add face recognition capabilities to their products.<ref name="ref_d829334f">[https://www.nxp.com/design/designs/nxp-edgeready-mcu-based-solution-for-face-recognition:MCU-FACE-RECOGNITION NXP EdgeReady MCU-Based Solution for Face Recognition]</ref>
 +
# “Face recognition is a very deceiving term, technically, because there’s no limit,” he concludes.<ref name="ref_f586bb6e">[https://www.ft.com/content/cf19b956-60a2-11e9-b285-3acd5d43599e Who’s using your face? The ugly truth about facial recognition]</ref>
 +
# It includes high-quality cameras and API that easily integrates face recognition analytics with existing technology systems.<ref name="ref_12b1fa13">[https://analyticsindiamag.com/9-best-facial-recognition-software-for-your-pc/ 9 Best Facial Recognition Software For Your PC]</ref>
 +
# We present data comparing state-of-the-art face recognition technology with the best human face identifiers.<ref name="ref_d827191e">[https://www.pnas.org/content/115/24/6171 Face recognition accuracy of forensic examiners, superrecognizers, and face recognition algorithms]</ref>
 +
# First, untrained “superrecognizers” from the general public perform surprisingly well on laboratory-based face recognition studies (1).<ref name="ref_d827191e" />
 +
# Second, wisdom-of-crowds effects for face recognition, implemented by averaging individuals’ judgments, can boost performance substantially over the performance of a person working alone (2⇓⇓–5).<ref name="ref_d827191e" />
 +
# Multiple laboratory-based face recognition tests of these individuals indicate that highly accurate face identification can be achieved by people with no professional training (1).<ref name="ref_d827191e" />
 +
# How Facial Recognition Algorithm Works Which algorithms are used in face recognition?<ref name="ref_e33990f3">[https://labelyourdata.com/articles/facial-recognition-algorithms-for-machine-learning/ Facial Recognition Algorithms for Machine Learning: Application and Safety]</ref>
 +
# There are more subtle ways in which face recognition algorithms are changing our everyday life in meaningful ways too, proving that this technology is still far from infallible.<ref name="ref_e33990f3" />
 +
# According to one aspect of the present technique, a system and method of face recognition is provided.<ref name="ref_fefb1c03">[https://www.google.com/patents/US20060120571 US20060120571A1 - System and method for passive face recognition - Google Patents]</ref>
 +
# A face recognition module identifies at least one likely candidate from a plurality of stored images based on the transformed model face.<ref name="ref_fefb1c03" />
 +
# 4 is a flow chart illustrating a face authentication process of the exemplary face recognition system illustrated in FIG.<ref name="ref_fefb1c03" />
 +
# Each time an image is captured, the face recognition system 10 may utilize the captured image during the face recognition process.<ref name="ref_fefb1c03" />
 +
# Humans show race bias in face recognition and this is a finding that has been replicated hundreds of times at this point.<ref name="ref_80fdaced">[https://www.afcea.org/content/accuracy-machines-facial-recognition The Accuracy of Machines in Facial Recognition]</ref>
 +
# Face recognition is a method of identifying or verifying the identity of an individual using their face.<ref name="ref_4ec9f848">[https://www.eff.org/pages/face-recognition Face Recognition]</ref>
 +
# Face recognition systems can be used to identify people in photos, video, or in real-time.<ref name="ref_4ec9f848" />
 +
# But face recognition data can be prone to error, which can implicate people for crimes they haven’t committed.<ref name="ref_4ec9f848" />
 +
# Additionally, face recognition has been used to target people engaging in protected speech.<ref name="ref_4ec9f848" />
 +
# This is where you can store your processed face recognition videos.<ref name="ref_18999172">[https://www.pyimagesearch.com/2018/06/18/face-recognition-with-opencv-python-and-deep-learning/ Face recognition with OpenCV, Python, and deep learning]</ref>
 +
# : This is where you can store your processed face recognition videos.<ref name="ref_18999172" />
 
===소스===
 
===소스===
 
  <references />
 
  <references />

2020년 12월 22일 (화) 23:23 판

노트

위키데이터

말뭉치

  1. Telpo Android OS face recognition machines have good compatibility and extensibility.[1]
  2. Further, because it is the first step in a broader face recognition system, face detection must be robust.[2]
  3. A face recognition system is expected to identify faces present in images and videos automatically.[2]
  4. The holistic approaches dominated the face recognition community in the 1990s.[2]
  5. There are perhaps four milestone systems on deep learning for face recognition that drove these innovations; they are: DeepFace, the DeepID series of systems, VGGFace, and FaceNet.[2]
  6. Considering roughly presented elements above of the complex process of face recognition, a number of limitations and imperfections can be seen.[3]
  7. It is the fact that face recognition systems are still not very robust regarding to deviations from ideal face image.[3]
  8. Recent advances in automated face analysis, pattern recognition and machine learning have made it possible to develop automatic face recognition systems to address these applications.[3]
  9. Being part of a biometric technology, automated face recognition has a plenty of desirable properties.[3]
  10. Research on face recognition to reliably locate a face in an image that contains other objects gained traction in the early 1990s with the principle component analysis (PCA).[4]
  11. LDA Fisherfaces became dominantly used in PCA feature based face recognition.[4]
  12. Some face recognition algorithms identify facial features by extracting landmarks, or features, from an image of the subject's face.[4]
  13. Other algorithms normalize a gallery of face images and then compress the face data, only saving the data in the image that is useful for face recognition.[4]
  14. Face recognition is a technology capable of identifying or verifying a subject through an image, video or any audiovisual element of his face.[5]
  15. The objective of face recognition is, from the incoming image, to find a series of data of the same face in a set of training images in a database.[5]
  16. Thanks to the use of artificial intelligence (AI) and machine learning technologies, face recognition systems can operate with the highest safety and reliability standards.[5]
  17. Face recognition uses focus on verification or authentication.[5]
  18. With the constant support of our dexterous crew of technocrats, we are fulfilling the varied requirements of clients by manufacturing and supplying optimum quality Face Recognition Machine.[6]
  19. We are actively engaged in offering high performance Face Recognition Machine, which is procured from certified vendors of the industry.[6]
  20. The offered face recognition machine is robustly designed by our reliable vendors in compliance with international quality standards.[6]
  21. This face recognition machine is widely used in various corporate sectors, offices, etc.[6]
  22. This article opens up what face recognition is from a technology perspective, and how deep learning increases its capacities.[7]
  23. Realizing the weaknesses of face recognition systems, data scientists went further.[7]
  24. By applying traditional computer vision techniques and deep learning algorithms, they fine-tuned the face recognition system to prevent attacks and enhance accuracy.[7]
  25. Deep learning is one of the most novel ways to improve face recognition technology.[7]
  26. Even though face recognition is promising, it does have some flaws.[8]
  27. Simple face recognition systems could easily be spoofed by using paper-based images from the internet.[8]
  28. Face recognition is only the beginning of implementing this method.[9]
  29. A classical 2D face recognition system operates on images or videos obtained from surveillance systems, commercial/private cameras, CCTV, or similar everyday hardware.[10]
  30. To sum up, all holistic methods are prevalent in the implementation of face recognition systems.[10]
  31. It is generally known that in this perspective, the variations in lighting that contemplate face recognition present one of the significant challenges.[10]
  32. Attention and fixations play a crucial function in human face recognition.[10]
  33. In this paper we study the performance of the one-against-all (OAA) and one-against-one (OAO) ELM for classification in multi-label face recognition applications.[11]
  34. Much like databases today, face recognition will be used for all sorts of things in many parts of societies, including many things that don’t today look like a face recognition use case.[12]
  35. We might be comfortable with our bank using face recognition as well.[12]
  36. Part of the experience of databases, though, was that some things create discomfort only because they’re new and unfamiliar, and face recognition is the same.[12]
  37. The cutting edge work is still limited to a relatively small number of companies and institutions, but ‘face recognition’ is now freely available to any software company to build with.[12]
  38. Face recognition is a method for identifying an unknown person or authenticating the identity of a specific person from their face.[13]
  39. Another approach to face recognition is to normalize and compress 2-D facial images, and to compare these with a database of similarly normalized and compressed images.[13]
  40. Three-dimensional face recognition uses 3-D sensors to capture the facial image, or reconstructs the 3-D image from three 2-D tracking cameras pointed at different angles.[13]
  41. Adding skin texture analysis to 2-D or 3-D face recognition can improve the recognition accuracy by 20 to 25 percent, especially in the cases of look-alikes and twins.[13]
  42. Built using dlib's state-of-the-art face recognition built with deep learning.[14]
  43. Face recognition can be done in parallel if you have a computer with multiple CPU cores.[14]
  44. The face recognition model is trained on adults and does not work very well on children.[14]
  45. MX RT106F crossover MCU, enabling developers to quickly and easily add face recognition capabilities to their products.[15]
  46. “Face recognition is a very deceiving term, technically, because there’s no limit,” he concludes.[16]
  47. It includes high-quality cameras and API that easily integrates face recognition analytics with existing technology systems.[17]
  48. We present data comparing state-of-the-art face recognition technology with the best human face identifiers.[18]
  49. First, untrained “superrecognizers” from the general public perform surprisingly well on laboratory-based face recognition studies (1).[18]
  50. Second, wisdom-of-crowds effects for face recognition, implemented by averaging individuals’ judgments, can boost performance substantially over the performance of a person working alone (2⇓⇓–5).[18]
  51. Multiple laboratory-based face recognition tests of these individuals indicate that highly accurate face identification can be achieved by people with no professional training (1).[18]
  52. How Facial Recognition Algorithm Works Which algorithms are used in face recognition?[19]
  53. There are more subtle ways in which face recognition algorithms are changing our everyday life in meaningful ways too, proving that this technology is still far from infallible.[19]
  54. According to one aspect of the present technique, a system and method of face recognition is provided.[20]
  55. A face recognition module identifies at least one likely candidate from a plurality of stored images based on the transformed model face.[20]
  56. 4 is a flow chart illustrating a face authentication process of the exemplary face recognition system illustrated in FIG.[20]
  57. Each time an image is captured, the face recognition system 10 may utilize the captured image during the face recognition process.[20]
  58. Humans show race bias in face recognition and this is a finding that has been replicated hundreds of times at this point.[21]
  59. Face recognition is a method of identifying or verifying the identity of an individual using their face.[22]
  60. Face recognition systems can be used to identify people in photos, video, or in real-time.[22]
  61. But face recognition data can be prone to error, which can implicate people for crimes they haven’t committed.[22]
  62. Additionally, face recognition has been used to target people engaging in protected speech.[22]
  63. This is where you can store your processed face recognition videos.[23]
  64. : This is where you can store your processed face recognition videos.[23]

소스

  1. ↑ Face Recognition Machine Manufacturer
  2. ↑ 2.0 2.1 2.2 2.3 A Gentle Introduction to Deep Learning for Face Recognition
  3. ↑ 3.0 3.1 3.2 3.3 Face Recognition: Issues, Methods and Alternative Applications
  4. ↑ 4.0 4.1 4.2 4.3 Facial recognition system
  5. ↑ 5.0 5.1 5.2 5.3 Face Recognition: how it works and its safety
  6. ↑ 6.0 6.1 6.2 6.3 Face Recognition Machine
  7. ↑ 7.0 7.1 7.2 7.3 Face Recognition App Development Using Deep Learning
  8. ↑ 8.0 8.1 How machine learning changed facial recognition technology?
  9. ↑ How to build a face detection and recognition system
  10. ↑ 10.0 10.1 10.2 10.3 Past, Present, and Future of Face Recognition: A Review
  11. ↑ Face recognition based on extreme learning machine
  12. ↑ 12.0 12.1 12.2 12.3 Face recognition and AI ethics — Benedict Evans
  13. ↑ 13.0 13.1 13.2 13.3 What is face recognition? AI for Big Brother
  14. ↑ 14.0 14.1 14.2 ageitgey/face_recognition: The world's simplest facial recognition api for Python and the command line
  15. ↑ NXP EdgeReady MCU-Based Solution for Face Recognition
  16. ↑ Who’s using your face? The ugly truth about facial recognition
  17. ↑ 9 Best Facial Recognition Software For Your PC
  18. ↑ 18.0 18.1 18.2 18.3 Face recognition accuracy of forensic examiners, superrecognizers, and face recognition algorithms
  19. ↑ 19.0 19.1 Facial Recognition Algorithms for Machine Learning: Application and Safety
  20. ↑ 20.0 20.1 20.2 20.3 US20060120571A1 - System and method for passive face recognition - Google Patents
  21. ↑ The Accuracy of Machines in Facial Recognition
  22. ↑ 22.0 22.1 22.2 22.3 Face Recognition
  23. ↑ 23.0 23.1 Face recognition with OpenCV, Python, and deep learning
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