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HOME ARCHIVES SPECIAL ISSUE I Peer Review Articles
Comparative analysis on deep convolutional neural network for
brain tumor data set
https://doi.org/10.53730/ijhs.v6nS1.4949
 R. Vinayaga Moorthy
 vinayagamoorthy3@gmail.com
 Research scholar, Department of Computer Science & Engineering,
Manonmaniam Sundaranar University, Tirunelveli, India
 A. Gopi Kannan
 Research scholar, Department of Computer Science & Engineering,
Manonmaniam Sundaranar University, Tirunelveli, India
 R. Balasubramanian
 Professor, Department of Computer Science & Engineering,
Manonmaniam Sundaranar University, Tirunelveli, India
Keywords: Deep Learning, CNN, LeNet, AlexNet, VGG Net-
16, ResNet-18
ABSTRACT
Deep Learning is a subdivision of machine learning and
Artificial intelligence (AI). Autonomous Deep learning
enables human brain to think and learn computers. In
recent days Deep learning is used in many domains,
especially in medical field. It is used mainly in classification.
The Convolutional Neural Network (CNN) is one among the
best technique in DL. It is best suitable in image
classifications. CNN is directed to process the data into
multiple layers of arrays. It is used for computationally
efficient. Brain Tumor is one of the dangerous diseases in
India as well as the whole world. A brain tumor is an
unwanted cell in the brain. Brain tumor symptoms are based
on size, location and type .There are two types of brain
tumor. Brain tumor tissue affects on the brain that is called
primary tumor. Brain tumor tissue affects in outside the
brain that is called as secondary tumor (metastatic).In this
paper, we are analyzing various Deep Convolution Neural
Network on brain tumor perspectives. Here, LeNet, AlexNet,
PDF
PUBLISHED
22-03-2022
HOW TO CITE
Moorthy, R. V., Kannan, A. G., &
Balasubramanian, R. . (2022). Comparative
analysis on deep convolutional neural
network for brain tumor data set.
International Journal of Health Sciences,
6(S1), 1917–1930.
https://doi.org/10.53730/ijhs.v6nS1.4949
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Special Issue I
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2. 7/4/22, 7:42 AM Comparative analysis on deep convolutional neural network for brain tumor data set | International journal of health sciences
https://sciencescholar.us/journal/index.php/ijhs/article/view/4949 2/5
ResNet-18, VGG Net-16 are discussed and Evaluation
metrics like Accuracy, F1 score, Precision, Recall are used to
identify the performance of the above techniques.
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CITESCORE 2021
2.0 2021
CiteScore
63rd percentile
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