Open AccessIceberg Detection in Satellite Images using Deep Learning Techniques
Author(s) -
A M Naveena,
Jason Prasad
Publication year - 2020
Publication title -
international journal of recent technology and engineering
Language(s) - English
Resource type - Journals
ISSN - 2277-3878
DOI - 10.35940/ijrte.f9736.038620
Subject(s) - iceberg , satellite , convolutional neural network , satellite imagery , identification (biology) , computer science , remote sensing , deep learning , geolocation , artificial neural network , artificial intelligence , geography , sea ice , engineering , meteorology , botany , aerospace engineering , biology , world wide web
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 network (CNN) model is proposed for the iceberg detection from the satellite images. It is based on the satellite dataset for target classification and target identification. The iceberg detection is based on the statistical criteria 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 wrongly classified as ship. This model is done to make accurate about the changes in the detection.