Single Shot Multi-Face Detection & Gender Recognition

5 Pages Posted: 11 Apr 2019

See all articles by Himanshu Vishwakarma

Himanshu Vishwakarma

Kamla Nehru Institute of Technology

Gargi Verma

Kamla Nehru Institute of Technology

Smita Singh

Kamla Nehru Institute of Technology

Arvind Kumar Tiwari

Kamla Nehru Institute of Technology

Date Written: March 11, 2019

Abstract

The method is proposed single shot face detection and gender recognition using Convolutional Neural Network(CNN).

The proposed method is using the YOLO algorithm to detect the human face and make gender recognition. The face detection and gender recognition are very interesting since the past two decades. This can be used in future for the security purpose, biometric, digital cosmetic and many more. As human face is a dynamic object having a high degree of variability in its appearance, that make the face detection problem difficult in the computer vision task. The goal of this paper is to multiple face detection and its gender recognition in one shot of image is passed in the network and give the better performance in term of speed and accuracy.

Suggested Citation

Vishwakarma, Himanshu and Verma, Gargi and Singh, Smita and Tiwari, Arvind Kumar, Single Shot Multi-Face Detection & Gender Recognition (March 11, 2019). Proceedings of 2nd International Conference on Advanced Computing and Software Engineering (ICACSE) 2019. Available at SSRN: https://ssrn.com/abstract=3350305 or http://dx.doi.org/10.2139/ssrn.3350305

Himanshu Vishwakarma (Contact Author)

Kamla Nehru Institute of Technology ( email )

SULTANPUR
UTTAR PRADESH
SULTANPUR
India

Gargi Verma

Kamla Nehru Institute of Technology ( email )

SULTANPUR
UTTAR PRADESH
SULTANPUR
India

Smita Singh

Kamla Nehru Institute of Technology ( email )

SULTANPUR
UTTAR PRADESH
SULTANPUR
India

Arvind Kumar Tiwari

Kamla Nehru Institute of Technology ( email )

SULTANPUR
UTTAR PRADESH
SULTANPUR
India

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