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Top 10 Real-Time Artificial Intelligence Applications You need to Know

Top 10 Real-Time Artificial Intelligence Applications You need to Know

In this digital world, latest and advanced technologies are arriving day by day.   With the advent of these technologies, latest and exorbitant gadgets are also entering in the market. Apple has offer latest face detection technology in latest iPhones version.  Face Identification must be needed to unlock your iPhones. It is optional lock which is used for the security purpose. In other case, imagine stand-up in front of the entry door of your office and see your face pop on a large screen.

If the display classifies you, it unlocks the doors; if it doesn’t, the doors don’t open. Your look/face is your digital ID. It permits you to go into your office and validate your individuality in a hoard of other places. Sounds weird, but is irrefutably remarkable! This is old method to becoming global. First of all, let’s discuss about face recognition and detection.

What is Face Recognition??

In the technology world of face detection and recognition system identifying the face various angles with even more accurateness than a person can.  Faces can be recognized perfectly and accurately with the help of machine learning and deep learning techniques. The facial recognition systems consist of hardware components of high-end along with capable software for documentation and confirmation of a person by associating the facial features from the person present to the types stored in the facial database. The facial detection and recognition system can authorize an individual from a digital image or frame/clips of a video. Numeric codes called face prints are used for detection along with identifying 80 nodal points on the face.

Face recognition technology is the least invasive and fastest biometric technology. It works with the most obvious individual identifier – the human face. As an alternative of requiring people to place their hand on a reader or exactly spot their eye in front of a scanner, face recognition systems inconspicuously take pictures of people’s faces as they arrive a well-defined area. There is no interruption or postponement, and in most cases the subjects are completely unaware of the process. They do not feel “under surveillance” or that their confidentiality has been conquered. There are various AI based software companies working on this technology.

Technology: Facial recognition examines the features of images of person’s faces and gives input through a digital video camera. It processes the complete facial structure, comprising distances between eyes, mouth and nose and jaw edges. These dimensions are kept in a database and used as a contrast when a user positions before the camera. This biometric has been extensively, and possibly passionately, touted as an eccentric system for recognizing potential but so far has not seen wide recognition in high-level usage. It is predictable that biometric facial recognition technology will soon overtake impression biometrics as the most general form of user verification. Each face has several, different breakthroughs, the dissimilar peaks and valleys that make up facial types. Each human face has around 80 nodal points. Some of these dignified by the Facial Recognition Technology are:

  1. Space between the eyes
  2. Nose Width
  3. Eye sockets depth
  4. Cheekbones Shapes
  5. The distance of the jaw line

These nodal points are measured making a numerical code, called a face print, on behalf of the face in the database.

 How it works: The following four-stage process demonstrates the method biometric systems function:

  1. Capture – a physical or interactive sample is taken by the system during registration.
  2. Extraction – unique data is taken out from the section and a template is produced
  3. Comparison – the template is then associated with a new sample
  4. Matching – the system then chooses if the types removed from the new sample are identical or not.

Whenever the user looks at the camera and is standing two feet away from it. The system will find the user’s face and execute matches in contrast to the demanded identity or the facial database. It is probable that the user may essential to change and reattempt the confirmation based on his facial position. The system typically originates to a choice in less than 5 seconds.

Application: Applications based on Web and desktop can also take profit from such facial recognition systems to escape from hacking. Enforcement agencies can use this for finding a single person in a crowd. Enterprises can maintain track of employee’s appearance. These systems are already being used by activities directing criminals, at airports for safety or to distinguish players during games. Marketing personalization makes use of billboards with software which recognize the demographics of spectators for targeted publicity. Various machine learning approaches can be applied over it to get the accurate results.

Specifications: Other specifications are as follow:

  1. No retraining: The training is typically done on the face and not to the obtainable images in the database.
  2. Self-supporting Feature Database: Post the training, the facial feature database need to be dissimilar from the face image database. This is typically complete to defend the interfering of descriptions in the facial database. Distance between, nose tips, jaw lines, lips contours, eye centers are all coordinated throughout the face detection and recognition process.
  3. Resolution dependent: Face Recognition algorithm and images must be self-governing of high resolution images; the videos though must be at or upper than 640*480 resolution.
  4. Robust: The face recognition system must be durable and not weak on the way to dissimilarities in posture, facial expressions.
  5. Accuracy: The face recognition must work at a tremendously high accuracy rate. It is always more than 90%.

In the nutshell, we can say that facial recognition tools along with additional technologies like geolocation software, police body cameras, and machine learning provide help in real-time tracking. Combining technologies offers good-looking options for crime fighting, and expands the openings in our privacy. Moreover, Apple and Google use it for sharing and tagging photos. Apart from some smart phone applications using this technology, Facebook also uses it for tagging photographs. At Webtunix AI, various advanced services related to the face detection and recognition are provided.

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