Open AccessPredicting Weather Conditions from Images
Author(s) -
Shonima Minhas and Shreya Kapoor
Publication year - 2020
Publication title -
international journal of modern trends in science and technology
Language(s) - English
Resource type - Journals
ISSN - 2455-3778
DOI - 10.46501/ijmtst061132
Subject(s) - convolutional neural network , computer science , field (mathematics) , artificial intelligence , image (mathematics) , pattern recognition (psychology) , contextual image classification , face (sociological concept) , artificial neural network , machine learning , mathematics , social science , sociology , pure mathematics
Convolutional neural networks (CNNs) are widely acknowledged in the fields of image and videorecognition, face recognition, image analysis, image classification and activity detection. CNNs take imagesas their input; assign adaptive weights and biases to numerous features of the image; and then assign thevarious categories to them.The intent of this paper is to establish a model to classify outdoor images to different weather classes.Literature survey about the field related to weather prediction has shown that the best results are obtainedwhile using the CNN models. This paper proposes a method of implementation of convolutional neuralnetworks to classify separate weather conditions into four classes, namely cloudy, rainy, shine and sunrise.In this paper, four CNN models with different number of model layers are implemented and their results areexamined.