Libraries at University of Nebraska-Lincoln



Face recognition is a new concept coming up lately and flourishing in the field of network access and multimedia information systems. Since humans are at the focus of attention in variety of applications containing videos, the concept of face recognition is rising in popularity. Several areas involving network security, retrieval and indexing of the content, and compression of videos gain a lot of benefit from the face recognition systems and related technology. Controlling the access of the networks with the help of facial recognition not only makes it difficult for the hackers to steal the information but also makes the system more fool proof, user friendly and manageable. Out of all the available tools for processing the biometric information, the face recognition system is the most popular one and used worldwide due to its ease of use and adaptability along with a wider range of working. The overall system may consist of hardware and software modules where in the detection of the facial features can be done using the available hardware and deep learning algorithms can be used to process the retrieved information. To this end, a system can be built considering face detection and face recognition as two major parts. This article shows the systematic bibliometric survey of the existing literature for the face recognition system using deep learning techniques. The survey is undertaken using the Scopus database for data analysis and several other tools like Gephi, science scape and minivan for visualisation of the fetched data. In this article, the information drawn from the Scopus database is articulated with respect to the vital aspects of bibliometric analysis such as documents fetched by affiliation, country or territory, funding sponsor, source, subject area, type and year. The information is then related to each other with the help of network diagrams for coappearance of information like - authors and source titles, authors and keywords, authors linked by co-publication etc. This survey reinforces the point that there are ample opportunities for the researchers to work in the field of face recognition system especially using deep learning techniques.