能见度
亮度
计算机科学
人工智能
亮度
卷积神经网络
计算机视觉
图像(数学)
差异(会计)
模式识别(心理学)
遥感
地理
光学
气象学
业务
会计
物理
作者
Shruti Chincholkar,Manoov Rajapandy
出处
期刊:Advances in intelligent systems and computing
日期:2019-10-19
卷期号:: 249-257
被引量:5
标识
DOI:10.1007/978-3-030-30465-2_28
摘要
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.
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