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Recent Advances in Computer Science and Communications


ISSN (Print): 2666-2558
ISSN (Online): 2666-2566

General Research Article

Performance Evaluation of Neural Network for Human Classification Using Blob Dataset

Author(s): Monika Mehta * and Madhulika Bhadauria

Volume 14, Issue 5, 2021

Published on: 12 September, 2019

Page: [1592 - 1602] Pages: 11

DOI: 10.2174/2666255813666190912101628

Price: $65


Background: Human Classification in public places is an emerging area in the applications of Computational Intelligence. Therefore, modeling of an optimal architecture of the neural network is required to classify them.

Methods: In this work for this purpose, blob dataset has been used to train the neural network. This dataset consists of 2408 features of a human blob.

Results: Further, analysis of this blob dataset has been done on the basis of various characteristic parameters for affirmation of actual training. During training and testing of this dataset, it has been observed that when nodes at hidden layer are below and above 10 then training of neural network is under fitted and overfitted respectively and works effectively when the nodes are 10 at the hidden layer.

Conclusion: From the experimental work performed in this study, an optimal neural network has been obtained to classify human using blob dataset.

Keywords: Computational intelligence, neural network, blob, classification, pattern recognition, underfitting, overfitting, hidden layer.

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