• Sunpreet Kaur Nanda
• Deepika Ghai

Abstract: Deep learning uses neural networks to learn efficient, properly knowledgeable representation of examples. For example, a pre-trained neural network can be used to identify and remove objects such as noise from pictures. Today, signal handling contemplates has definitely augmented its extension as contrasted and just a few years back, and framework picking up information on has been a basic specialized spot of the sign preparing society. Since 2006, profound learning another spot of device acing examines has developed, affecting a wide assortment of sign and insights preparing work in the customary and the new, augmented extensions. Different workshops, alongside 2009 ICML Workshop on Learning Feature Hierarchies; 2008 NIPS Deep Learning Workshop: Foundations and Future Directions; and 2009 NIPS Workshop on Deep Learning for Speech Recognition and similar applications, despite an up-and-coming extraordinary problem on the fundamental handling of speech and language in IEEE Transactions on Audio, Speech, and Language Processing (2010), have been directed explicitly to profound becoming more acquainted with and its projects to old style sign preparing zones.

Keywords: Deep learning, Image processing, Neural Network.

"Deep Learning for Image Processing", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 1, page no.1338-1341, January 2019, Available :http://www.jetir.org/papers/JETIRDW06216.pdf

"Deep Learning for Image Processing", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 1, page no. pp1338-1341, January 2019, Available at : http://www.jetir.org/papers/JETIRDW06216.pdf