Multi-Scene Recognition in Single Aerial Images Using CNN

Abstract

Scene recognition from aerial images is a primary application in utilizing high resolution satellite images. In the recent past, many studies were carried out in this field to classify an image to one scene category. But the real scenarios are different, they often contain more than one scene. Therefore, we explore an approach to recognize multiple scenes from a single aerial image. To do this, three different datasets namely UCM dataset, AID dataset and MAI dataset consisting of 2100, 10000, 3923 images respectively were used. Out of the three datasets, UCM and AID dataset are Single scene datasets and the MAI dataset is a multi-scene dataset. These datasets are utilized in two configurations namely UCM2MAI and AID2MAI. Prototype based memory network using different CNN baseline models is used as the backbone. First, the single scene datasets were used to extensively train different baseline models and store them as prototypes in the external memory. Experiments were conducted to analyse the performance of different baseline models.