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- EGMT-CD: Edge-Guided Multimodal Transformers Change Detection from Satellite and Aerial Images
- 作者： Yunfan Xiang Xiangyu Tian Yue Xu Xiaokun Guan Zhengchao Chen 来源： Remote Sensing 年份： 2023 文献类型 ： 期刊 关键词： sensing detection images edge Transformer feature change remote alignment heterogeneous
- 描述： Change detection from heterogeneous satellite and aerial images plays a progressively important role in many fields, including disaster assessment, urban construction, and land use monitoring. Currently, researchers have mainly devoted their attention to change detection using homologous image pairs and achieved many remarkable results. It is sometimes necessary to use heterogeneous images for change detection in practical scenarios due to missing images, emergency situations, and cloud and fog occlusion. However, heterogeneous change detection still faces great challenges, especially using satellite and aerial images. The main challenges in satellite and aerial image change detection are related to the resolution gap and blurred edge. Previous studies used interpolation or shallow feature alignment before traditional homologous change detection methods, which ignored the high-level feature interaction and edge information. Therefore, we propose a new heterogeneous change detection model based on multimodal transformers combined with edge guidance. In order to alleviate the resolution gap between satellite and aerial images, we design an improved spatially aligned transformer (SP-T) with a sub-pixel module to align the satellite features to the same size of the aerial ones supervised by a token loss. Moreover, we introduce an edge detection branch to guide change features using the object edge with an auxiliary edge-change loss. Finally, we conduct considerable experiments to verify the effectiveness and superiority of our proposed model (EGMT-CD) on a new satellite–aerial heterogeneous change dataset, named SACD. The experiments show that our method (EGMT-CD) outperforms many previously superior change detection methods and fully demonstrates its potential in heterogeneous change detection from satellite–aerial images.
- EGMT-CD: Edge-Guided Multimodal Transformers Change Detection from Satellite and Aerial Images
- 作者： Yunfan Xiang Xiangyu Tian Yue Xu Xiaokun Guan Zhengchao Chen 来源： Remote Sensing 年份： 2023 文献类型 ： 期刊 关键词： sensing detection images edge Transformer feature change remote alignment heterogeneous
- 描述： Change detection from heterogeneous satellite and aerial images plays a progressively important role in many fields, including disaster assessment, urban construction, and land use monitoring. Currently, researchers have mainly devoted their attention to change detection using homologous image pairs and achieved many remarkable results. It is sometimes necessary to use heterogeneous images for change detection in practical scenarios due to missing images, emergency situations, and cloud and fog occlusion. However, heterogeneous change detection still faces great challenges, especially using satellite and aerial images. The main challenges in satellite and aerial image change detection are related to the resolution gap and blurred edge. Previous studies used interpolation or shallow feature alignment before traditional homologous change detection methods, which ignored the high-level feature interaction and edge information. Therefore, we propose a new heterogeneous change detection model based on multimodal transformers combined with edge guidance. In order to alleviate the resolution gap between satellite and aerial images, we design an improved spatially aligned transformer (SP-T) with a sub-pixel module to align the satellite features to the same size of the aerial ones supervised by a token loss. Moreover, we introduce an edge detection branch to guide change features using the object edge with an auxiliary edge-change loss. Finally, we conduct considerable experiments to verify the effectiveness and superiority of our proposed model (EGMT-CD) on a new satellite–aerial heterogeneous change dataset, named SACD. The experiments show that our method (EGMT-CD) outperforms many previously superior change detection methods and fully demonstrates its potential in heterogeneous change detection from satellite–aerial images.
- 基于神经网络的遥感图像飞机实时检测算法
- 作者： 刘志 杨江涛 许新云 来源： 工业控制计算机 年份： 2024 文献类型 ： 期刊 关键词： 遥感图像 注意力机制 YOLOv4 MobileNetv3 深度可分离卷积
- 描述： 情况下，减少参数量；同时在路聚合网络（PANet）中使用深度可分离卷积代替传统卷积；在主干网络中引入BAM注意力机制，提高整体模型的泛化能力。然后对NMS网络进行了优化，以提升模型的最终识别精度。最后在
- 基于BiGRU-Attention改进的航空设备故障知识图谱构建
- 作者： 陈勇刚 刘康妮 王帅 来源： 航空学报 年份： 2024 文献类型 ： 期刊 关键词： 注意力机制 双向门控循环神经网络 故障诊断 航空设备故障 知识图谱
- 描述： 针对航空设备故障数据量庞大且传统故障诊断方法低效的问题，利用知识图谱技术构建高性能图数据库来替代传统民机所用的关系数据库以提高故障诊断决策效率，并通过一种以注意力机制（Attention）结合