An Improvised CNN Approach for the Classification of Icebergs in Satellite Images using Deep Learning

  • Raghuvira Pratap A, Babu Sallagundla, Prasad J V D

Abstract

Iceberg detection is found to be more critical in the previous researchers. High quality satellite monitoring of dangerous ice formations is critical to navigation safety and economic activity in the regions. The satellite images play a crucial role in the identification of the icebergs. In this manuscript, a Convolutional Neural Networks(CNN) model is proposed for the iceberg identification from the satellite images. It is based on the satellite dataset for target classification and target identification. The iceberg discovery is based on the statistical basis is for finding the satellite images. This model is used to identify automatically whether it is remote sensed target is iceberg or not. Sometimes the iceberg is erroneously classified as ship. This model is done to make accurate about the changes in the detection.

 Keywords: Convolutional neural network (CNN), Iceberg detection, satellite images, target classification.

Published
2020-05-06
How to Cite
Raghuvira Pratap A, Babu Sallagundla, Prasad J V D. (2020). An Improvised CNN Approach for the Classification of Icebergs in Satellite Images using Deep Learning. International Journal of Advanced Science and Technology, 29(06), 3011 - 3019. Retrieved from https://sersc.org/journals/index.php/IJAST/article/view/13835