This paper is published in Volume-6, Issue-6, 2020
Area
Engineering
Author
Jayanth H. N.
Org/Univ
New Horizon College of Engineering, Bengaluru, Karnataka, India
Pub. Date
04 December, 2020
Paper ID
V6I6-1184
Publisher
Keywords
Image Classification, CNN, RGB Image

Citationsacebook

IEEE
Jayanth H. N.. Natural scene image classification using CNN, International Journal of Advance Research, Ideas and Innovations in Technology, www.IJARIIT.com.

APA
Jayanth H. N. (2020). Natural scene image classification using CNN. International Journal of Advance Research, Ideas and Innovations in Technology, 6(6) www.IJARIIT.com.

MLA
Jayanth H. N.. "Natural scene image classification using CNN." International Journal of Advance Research, Ideas and Innovations in Technology 6.6 (2020). www.IJARIIT.com.

Abstract

Research mainly focused on CNN model for feature extraction and classification of Images. Convolutional Neural Network (CNN) has demonstrated promising performance in image classification tasks. In this project, the algorithm is used to classify the images or natural scenes into 6 classes. This model at last predicts the accuracy or probabilities of different class labels and this probability is used for the predicting class at the end. This dataset is used for both training and testing purpose. It provides the accuracy rate 84.93%. Images with combination of two scenes creates and ambiguity hence it is difficult for model to classify. Therefore, it leads to failure in algorithm sometimes. Images used in the training purpose are RGB images. The computational time for processing these images is relatively high as compare to other normal images. Stacking the model with more layers and training the network with more image data using clusters of GPUs provide more accurate results of classification of images.
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