• Marie Fernandes

In recent era and research studies, the deep learning apart from being a subpart of the most technological advance area of the machine learning that believes in learning from example for producing result with higher emphasis on accuracy same as human instinct. Glaucoma is a silent and neuro-degenerative eye disease which is irreversible and is considered as the primary reason of vision loss. As per World Health Organization (WHO), glaucoma is affecting more than 65 million people in the world ans so its early detection and treatment are far much more important so as to prevent vision loss. This eye disease has a major setback of optic nerve fibre loss that is due to increased intraocular pressure (IOP) or can be said in simple words that due to loss of blood flow to the optic nerve. It has been noted that IOP measurement is cannot be specific nor it is sensitive to be an effective indicator or highly noted measured valued as it has been noted that visual damage can also occur even without increased IOP. So, the early detection of glaucoma through machine learning, artificial intelligence application of deep learning is highly one of the computer aids available that can help ophthalmologists in this area. In this paper, we present study of the deep learning technique with different CNN architectures which can be used for glaucoma assessment.

Glaucoma, machine learning, artificial intelligence, deep learning, convolution neural network

"A STUDY OF DEEP LEARNING METHODS", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.8, Issue 10, page no.f158-f164, October-2021, Available :http://www.jetir.org/papers/JETIR2110524.pdf

"A STUDY OF DEEP LEARNING METHODS", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.8, Issue 10, page no. ppf158-f164, October-2021, Available at : http://www.jetir.org/papers/JETIR2110524.pdf