Face Spoofing Using Deep Learning

Project Code :TCMAPY515

Objective

The main objective of this paper is to propose a novel framework based on the Convolutional Neural Network for the face anti-spoofing problem, which is inspired by the philosophy used by humans to determine whether a presented face example is genuine or not, namely, to look at the example globally first and then carefully observe the local regions to gain more discriminative information (CNN).

Abstract

We propose a novel framework based on the Convolutional Neural Network for the face anti-spoofing problem, which is inspired by the philosophy used by humans to determine whether a presented face example is genuine or not, namely, to look at the example globally first and then carefully observe the local regions to gain more discriminative information (CNN). Specifically, we use deep learning to mimic the behavior of discovering face-spoofing-related information from image sub-patches. 

NOTE: Without the concern of our team, please don't submit to the college. This Abstract varies based on student requirements.

Block Diagram

Specifications

H/W System Configuration:

Processor                  -    I5/Intel Processor

RAM                           -    8GB (min)

Hard Disk                  -   500GB

S/W System Configuration:

Operating System        :  Windows 10

Server side Script         :  Python

Framework                    : Django, Flask


Learning Outcomes

Learning Outcomes

What is Deep Learning?

Abut Deep Learning algorithms.

About CNN.

Knowledge on PyCharm Editor


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