Detection Of Ships in The Ocean Using Deep Learning Algorithm

Maritime transportation is one of the most common and growing transportation schemes in the ocean. Autonomous ships have grown in popularity since the introduction of self-driving autos, particularly the submarines as well as weapon equipped ships that uses by military persons. Ship recognition and categorization in remote sensing photos is important for the security of marine-areas, also some more activities like peoples who use to catch fishes illegally and to control or to view the pollution in the sea. The detection and categorization of ships in remote sensing pictures is vital for maritime safety as well as other applications like traffic surveillance, illicit fishing and their prevention (sea). With the increasing number of satellite image data, automatic ship identification and remote sensor picture classification is an essential application for both the military and civic sectors, but there are many problems like clouds, weather which cause distraction. So, in this paper we have suggested a deep learning model which is based on CNN that is convolutional neural net. By using CNN, we can increase throughput, efficiency & also remote sensing picture which is used for image processing is fast and reliable.