Deep Learning is the crux of face recognition. Using deep, feed-forward artificial neural networks, you can create a face recognition system that can detect and verify faces with different poses, emotions, and lighting conditions.
The goal here is to get a deep neural network to output a person’s face, along with its identification. The neural network needs to be trained to automatically identify different features of a face and calculate numbers based on that. We can consider this output of the neural network to be an identifier for a person’s face. If you input different images of the same person, the output of the neural network will be very similar. On the other hand, if you input images of a different person, the output will be very different.
Join our webinar to understand how this technology is disrupting almost every industry from banking and healthcare to defense, which is why it is well worth everyone’s time to discuss its techniques and applications.
Mukul Joshi is an accomplished computer scientist. He possesses deep expertise in the fields of machine learning, data mining, and data science. Mukul is a highly sought-after guest lecturer. He has delivered a lecture about IoT and ML for predictive maintenance at the InterSystems Global Summit in 2018.
He has also delivered a lecture about scalable ways of deploying ML modules at Globant, as well as a discourse on the factory of the future at the Confederation of Indian Industry (CII). He has two patents to his name and has been published extensively in his fields of expertise. Mukul is an alumnus of IIT Bombay.