Scopus Indexed Publications

Paper Details

Nationality Detection Using Deep Learning
Md. Abrar Hamim, Jeba Tahseen, Kazi Md Istiyak Hossain, Saurav Das,

A new intelligent monitoring model is developed by us for determining gender and nationality from frontal picture candidates utilizing the face area based on deep learning. Face recognition is influenced by a number of characteristics, including picture quality, illumination, rotation angle, blockage, and facial expression. As a result, we must first recognize an input image before converting it to a genuine input. Nationality is the most well distinguishing characteristic that is applied in every nation, and it is also important to secure authentication. Image detection is crucial in this case. Then, we can determine the facial shape, gender, and nationality of the candidate image. In the end, we return the result based on the distance comparison using the use of a library to measure the sample. There were significant discrepancies across photographs while measuring samples based on their gender and facial features. The photos used in the input must be the same as those used in the output. Picture of a frontal face with clean lighting and no blemishes at every angle of rotation. The model may be used by ordinary people, models, celebrities, actors, and others. In the end, computer can tell nationality by looking at a picture of a person’s face.

"Face detection Image detection Face shapes Gender detection Nationality recognition"
Journal or Conference Name
Lecture Notes on Data Engineering and Communications Technologies
Publication Year