Open-World Recognition in Remote Sensing: Concepts, challenges, and opportunities

In recent years, remote sensing recognition technology has found extensive applications in diverse fields, such as modern agriculture, forest management, urban planning, natural resource management, and disaster monitoring. However, the existing remote sensing recognition tasks face significant challenges because of the complex and ever-changing observation environment and the rapid growth of observation classes. The detection performance of existing closed-set recognition methods (where the test set does not contain unknown classes) is greatly limited. Therefore, numerous remote sensing open-set recognition (RSOSR) methods have been proposed to cope with more demanding but practical scenarios in the open world, including scenes or targets with unknown classes. Despite this, there is still a lack of comprehensive work on RSOSR technology. This article presents a comprehensive review of existing RSOSR technologies, covering relevant definitions, model principles, evaluation standards, and method comparisons. We then identify and discuss the limitations of current RSOSR technologies while highlighting promising research directions.