人工智能用于遥感目标可靠性识别:总体框架设计、现状分析及展望

Artificial intelligence for reliable object recognition from remotely sensed data:overall framework design,review and prospect

可靠性是遥感监测的重要研究方向之一。人工智能技术促进了遥感目标识别技术的快速发展,但是其不可解释性带来了新的问题。本文依据空间数据的可靠性理论和人工智能基础理论,首先,提出了智能化遥感目标可靠性识别思想及总体框架;然后,阐述了影响可靠性的因素分析、可靠性提升方法、可靠性评估方法和可靠性过程控制等核心研究方向;最后,展望了人工智能用于遥感目标可靠性识别方法的未来发展方向。

Reliability is one of the important features in remotely sensed data-based land use monitoring.Artificial intelligence(AI)technology promotes the rapid development of object recognition from remotely sensed data.However,the un-explainability in such image processing causes reliability problems.Based on the reliability theory and the basic theory of AI,this paper first presents the idea and the overall framework of intelligent and reliable object recognition.Second,the core research directions,including analysis of influencing factors,improvement methods,evaluation methods,and process control for reliability are sequentially introduced.Finally,the future development trend of AI for reliable object recognition from remotely sensed data is outlined.