文章基本信息

标题：Future Face Predictor using Generative Adversarial Networks
本地全文：下载
作者：Shanta Sondur ; Ronit Bhatia ; Anirudh Iyer 等
期刊名称：International Journal of Advances in Engineering and Management
电子版ISSN：2395-5252
出版年度：2020
卷号：2
期号：4
页码：490-495
DOI：10.35629/5252-0204463466
语种：English
出版社：IJAEM JOURNAL
摘要：This report presents a generalized and effective methodology for predicting how a missing person would look after a given number of years into the future. The disappearance of people is a matter of grave concern which occurs at an alarming rate in metropolitan cities like Mumbai. A missing person is defined as a person who has disappeared and whose status as alive or dead can’t be confirmed, as their location and fate are unknown. This paper aims to devise a method which predicts how a missing person will look after a certain number of years into the future given a photograph of the person. The purpose of this project is to help the Police authorities in finding people who have been missing for a long period of time, for whom it’s near impossible to find a recent image, while keeping a log of all the missing persons . In addition to this, their appearance may change as they age, which adds to the problem. The image of the missing person is predicted by the use of generative adversarial networks- a class of machine learning frameworks.