Paper intros

"Identifying race, which is a major physical feature in humans, is still a challenging task owing much to the lack of a concrete definition of race and the diversity of population across the globe." (Race estimation with deep networks)

"Recently, computer vision-based face image analysis has sparked considerable interest in a variety of applications such as surveillance, security, biometrics and so on. The goal of the facial analysis was to derive facial soft biometrics such as identification, gender, age, ethnicity, expression and so on. Among these, ethnicity recognition remains a hot study topic, a major aspect of society with profound linkages to a variety of environmental and social concerns." (Intelligent deep learning based ethnicity recognition and classification using facial images)

"In the last decade, there has been a surge of interest in addressing complex Computer Vision (CV) problems in the field of face recognition (FR). In particular, one of the most difficult ones is based on the accurate determination of the ethnicity of mankind." (Face recognition based on deep learning and FPGA for ethnicity identification)

"Race classification has been a long-term challenge in the field of face recognition recently. As it is a key-demographic trait of individuals, it has been employed in realworld applications; for example, surveillance videos and online advertisement, HumanComputer Interaction, law enforcement, and demographic and biometric research." (Ethnicity classification from face images, literature review)

"Ethnic conflicts frequently lead to violations of human rights, such as genocide and crimes against humanity, as well as economic collapse, governmental failure, environmental problems, and massive influxes of refugees. Many innocent people suffer as a result of violent ethnic conflict. People’s ethnicity can pose a threat to their safety. There have been many studies on the topic of how to categorize people by race. Until recently, the majority of the work on face biometrics had been conducted on the problem of person recognition from a photograph. However, other softer biometrics such as a person’s age, gender, race, or emotional state are also crucial. The subject of ethnic classification has many potential uses and is developing rapidly." (classification of ethnicity using efficient CNN models on MORPH and FERET datasets based on face biometrics)

"Human face and facial features gain a lot of attention from researchers and are considered as one of the most popular topics recently. Features and information extracted from a person are known as soft biometric, they have been used to improve the recognition performance and enhance the search engine for face images, which can be further applied in various fields such as law enforcement, surveillance videos, advertisement, and social media profiling." (a classification of arab ethnicity based on face image using deep learning approach)