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Indian Journal of Public Health Research & Development
Year : 2018, Volume : 9, Issue : 11
First page : ( 742) Last page : ( 747)
Print ISSN : 0976-0245. Online ISSN : 0976-5506.
Article DOI : 10.5958/0976-5506.2018.01550.4

Opportunities for applying deep learning networks to tumour classification

Kumar S Naresh1, Kumar P Pramod2, Sandeep CH3, Shwetha S4

1Assistant Professor, Department of CSE, S R Engineering College, Warangal

2Senior Assistant Professor, Research Scholor, Osmania University

3Research Scholor Associate Professor, Department of CSE, S R Engineering College, SR University, Warangal

4Assistant Professor, Department of CSE, Sumathi Reddy Institute of Technology and Science, Warangal, India

Online published on 7 December, 2018.


This paper investigates the opportunities for applying deep learning networks to tumor classification. It finds that basic networks can be found to convey sensible performance, equivalent with mid-run entertainers on the same dataset. Model saturation is a significant issue which can be settled by a combination of limiting the quantity of parameters in the model, include ensuring that training data is adjusted amongst positive and negative perceptions, low learning rates, and iteratively biasing the input data towards cases that the model has mis-arranged after past training epochs.



Deep learning networks, CNN, tumour classification.


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