Sea-Ice Scene Classification Using Aerial Images in Arctic Based on Transfer Learning

Arctic travel has become a significant way for commercial or scientific researches. Sea-ice is always serious threat for Arctic navigation. In this paper, a classification method of aerial images is proposed to recognize different types of sea-ice scenes, which can be further used to analyze the threat of each scene in Arctic Ocean. However, due to the diverse types and distribution of sea-ice in various scenes, the categories of sea-ice scenes are indistinct. So a grouping way is primarily introduced to define different sea-ice scenes. These scenes are grouped into six typical categories according to the distribution of sea-ice. Then a transfer learning strategy is used to fine-tune a pre-trained deep convolution neural network model. Finally, using that trained network to classify new sea ice scenes. Experimental results show that an acceptable classification accuracy can be obtained.