Regularized CNN Model for Crop Classification


Authors : Kavita Bhosle, Vijaya Musande

Volume/Issue : Volume 5 - 2020, Issue 1 - January

Google Scholar : https://goo.gl/DF9R4u

Scribd : https://bit.ly/30H0eRu

In this paper we have compared regularized Convolutional Neural Network (CNN) with without regularized CNN. This model is now becomes popular for many applications. It is used for classification, identification of object. The main advantage Deep learning CNN is that it can be used for unstructured video, audio, image data. Remote sensing data is highly unstructured data. EO-1 hyperspectral data has been used for the study of crop classification. It has been observed that classification accuracy is 75 % and test loss is 43.3 %.

Keywords : Convolutional Neural Network, Deep Learning, Land Use Land Cover.

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