Fog Image Classification and Visibility Detection Using CNN

6Citations
Citations of this article
7Readers
Mendeley users who have this article in their library.
Get full text

Abstract

The paper aims to find an approach for predicting the visibility percentage of the foggy images based on the factors like image brightness, luminance, intensity, and variance. The scope of using an image for predicting weather and providing information about the other details i.e. predicting if weather is foggy has increased. The idea is to utilize the data images to firstly classify them as being foggy or not. Secondly to detect the image visibility based on the image of a particular location. Thus the paper presents the implementation of convolutional neural network for the task of detecting and classifying the images into fog and non-fog. After getting the classification output, the brightness, luminance, variance and intensity of the images is calculated to find the visibility percent of the fog images.

Cite

CITATION STYLE

APA

Chincholkar, S., & Rajapandy, M. (2020). Fog Image Classification and Visibility Detection Using CNN. In Advances in Intelligent Systems and Computing (Vol. 1039, pp. 249–257). Springer. https://doi.org/10.1007/978-3-030-30465-2_28

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free