Deep Convolutional Neural Networks (CNN) for Medical Image Analysis
N. Deepa1, SP.Chokkalingam2
1N.Deepa, Assistant Professor, Department of CSE, Saveetha School of Engineering, SIMATS, Chennai (Tamil Nadu), India.
2SP.Chokkalingam, Professor, Department of CSE, Saveetha School of Engineering, Chennai (Tamil Nadu), India.
Manuscript received on 29 May 2019 | Revised Manuscript received on 11 June 2019 | Manuscript Published on 22 June 2019 | PP: 607-610 | Volume-8 Issue-3S, February 2019 | Retrieval Number: C11290283S19/19©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Deep learning plays an important role in prediction and analytical process. Deep learning applications are recognizing patters, recognizing speech, NLP (Natural Language Processing), etc. It is a subset of machine learning and its techniques raise research interests as it solves many problems which could not be approached before. This paper provides detailed analysis of deep learning and its techniques used in various applications and especially to provide an extensive reference for the researchers in deep learning and its algorithms, implementation techniques and applications used in recent technologies. This paper will also help to improve investigation of deep learning and highlights new research areas and advancements of technology.
Keywords: Image Analysis Neural Networks Deep Learning Analysis.
Scope of the Article: Deep Learning