• D.BHARADWAJA
• Dr.P.SREENIVASULU

Face recognition has become a fascinating field for researchers. The motivation behind the enormous interest in the topic is the need to improve the accuracy of many real-time applications such as identity authentication, access control surveillance. The complexity of the human face and the changes due to different effects make it more challenging to design as well as implement a powerful computational system for human face recognition. Face recognition is an important biometric that is used to uniquely identify an individual. However, the presence of various disguises in the face will diminish the performance of any facial recognition system. Disguised face recognition problem becomes extremely challenging when important facial features get covered up. Because of the increase in popularity and success of deep learning in computer vision problems, features learned by Convolutional Neural Networks (CNN) can be used for face recognition. Recognition is done by using a pre-trained Convolutional Neural Network (Alex-Net Model) for facial feature extraction. A new ORL dataset of covered faces has also been introduced for training the deep networks, this indeed is very useful for law enforcement and other organizations like security, bio-metric as it would help to identify criminals, Protestants.

Face Recognition, Convolutional Neural Network, AlexNet.

"FINE TUNING BASED AUTOMATIC FACE RECOGNITION SYSTEM USING ALEXNET", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 6, page no.889-899, June 2019, Available :http://www.jetir.org/papers/JETIR1907Q33.pdf

"FINE TUNING BASED AUTOMATIC FACE RECOGNITION SYSTEM USING ALEXNET", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 6, page no. pp889-899, June 2019, Available at : http://www.jetir.org/papers/JETIR1907Q33.pdf