Detection of Ship from Satellite Images Using Deep Convolutional Neural Networks with Improved Median Filter

Abstract

Detection of maritime object is of greater attention in the field of satellite image processing applications in order to ensure the security and traffic control. Even though several approaches were built in the past few years, still it requires proper revamp in the architecture to focus toward the reduction of barriers to improve the performance of ship identification or appropriate vessel detection. The inference due to cluttered scenes, clouds, and islands in between the ocean is the greater challenge during the classification of ship or vessel. In this paper, we proposed a novel ship detection method called deep neural method which works very faster and based on the concept on deep learning methodology. Experimental results provide the better accuracy, and time complexity also reduces little further when compared to the traditional method.