Wang Ruikun, Ma Lei, He Guangjun, Johnson Brian Alan, Yan Ziyun, Chang Ming, Liang Ying
Beijing Institute of Satellite Information Engineering, Beijing 100095, China.
State Key Laboratory of Space-Ground Integrated Information Technology, Space Star Technology Co., Ltd., Beijing 100095, China.
Sensors (Basel). 2024 May 29;24(11):3495. doi: 10.3390/s24113495.
Research on transformers in remote sensing (RS), which started to increase after 2021, is facing the problem of a relative lack of review. To understand the trends of transformers in RS, we undertook a quantitative analysis of the major research on transformers over the past two years by dividing the application of transformers into eight domains: land use/land cover (LULC) classification, segmentation, fusion, change detection, object detection, object recognition, registration, and others. Quantitative results show that transformers achieve a higher accuracy in LULC classification and fusion, with more stable performance in segmentation and object detection. Combining the analysis results on LULC classification and segmentation, we have found that transformers need more parameters than convolutional neural networks (CNNs). Additionally, further research is also needed regarding inference speed to improve transformers' performance. It was determined that the most common application scenes for transformers in our database are urban, farmland, and water bodies. We also found that transformers are employed in the natural sciences such as agriculture and environmental protection rather than the humanities or economics. Finally, this work summarizes the analysis results of transformers in remote sensing obtained during the research process and provides a perspective on future directions of development.
2021年后开始增多的关于遥感（RS）中变压器的研究，正面临相对缺乏综述的问题。为了解变压器在遥感中的发展趋势，我们对过去两年关于变压器的主要研究进行了定量分析，将变压器的应用分为八个领域：土地利用/土地覆盖（LULC）分类、分割、融合、变化检测、目标检测、目标识别、配准以及其他领域。定量结果表明，变压器在LULC分类和融合方面实现了更高的精度，在分割和目标检测方面性能更稳定。结合LULC分类和分割的分析结果，我们发现变压器比卷积神经网络（CNN）需要更多参数。此外，还需要进一步研究推理速度以提高变压器的性能。经确定，我们数据库中变压器最常见的应用场景是城市、农田和水体。我们还发现变压器应用于农业和环境保护等自然科学领域，而非人文或经济领域。最后，这项工作总结了研究过程中获得的变压器在遥感方面的分析结果，并提供了未来发展方向的展望。
