Neural Networks in Facial Recognition


Artificial neural networks are the main components of facial recognition technology, which is the most popular form of biometric identification today. Face recognition technology is applied in various fields: state security, marketing, and various mobile applications. It can be used instead of ID cards for international travel, social media, laptop webcam accessibility, and even providing secure entry into workplace buildings. Moreover, today’s systems can recognize a person, regardless of hairstyle or the presence of eyeglasses.

Neural networks are used in a wide variety of applications, not just recognizing faces, images and texts. They can be used for speech and audio signal recognition, in satellite maps, and even medical images (X-rays, MRI scans). Another promising development is emotion recognition. Analyzing users’ reaction to the content or information helps to improve interactions with customers and employees while working online. Services based on facial recognition can help during online learning: they can discern if a student is distracted during the exam, is actively cheating, or uses verbal prompts. Neural net is actively used in security system, i.e. tracking suspicious banking transactions and video surveillance systems.

Yet, it is still possible to optimize and increase functionality of neural networks, as they can be endlessly improved. There are some problems in facial recognition, including lighting issues, aging of the subjects, and the position of the head in space, and specialists are actively working on resolving these. For example, if just one year has passed since the last snapshot, the recognition percentage decreases to 50%.

The world of AI and machine learning can be daunting. Creating your own facial recognition system requires advanced knowledge of artificial neural networks and complex algorithms. So, turn to the experts and enlist one of Viaduct’s experienced IT specialists to help make your idea a reality!