基于零拍摄草图的远程传感图像检索,基于交叉模式的融合
Yang Liu1, Yuhao Dang2, Huaizhou Qi2
1The School of Telecommunications Engineering, Xidian University, Xi'an 710071, China; Key Laboratory of Social Computing and Cognitive Intelligence (Dalian University of Technology), Ministry of Education, Dalian, Liaoning 116024, China; MOE-LCSM, School of Mathematics and Statistics, Hunan Normal University, Changsha, Hunan 410081, China.
概括
使用草图获取遥感图像是具有挑战性的,因为数据稀缺和领域差距. 这项研究引入了一种新型的融合网络,利用边缘特征和语义信息来改进基于零拍摄草图的远程传感图像检索 (ZS-SBRSIR).
科学领域:
- 计算机科学 计算机科学
- 遥感 遥感 遥感 遥感
- 人工智能的人工智能
背景情况:
- 基于草图的图像检索 (SBIR) 允许用户使用手绘草图找到图像.
- 当没有示例图像可用时,零拍摄SBIR (ZS-SBIR) 非常重要.
- 对于遥感数据的ZS-SBIR (ZS-SBRSIR) 面临挑战,因为草图数据稀缺,并且存在显著的域间隙.
研究的目的:
- 解决目前基于零拍摄草图的遥感图像检索 (ZS-SBRSIR) 的局限性.
- 开发一个新的网络,有效地弥合了草图和遥感图像之间的领域差距.
- 提高ZS-SBRSIR模型的概括能力.
主要方法:
- 为ZS-SBRSIR引入了一种新的零射击交叉模式融合网络.
- 从遥感图像中提取的边缘特征作为桥梁模式,更接近草图.
- 利用现有的图像标签进行对比训练,以纳入语义信息.
主要成果:
- 拟议的模型有效地利用多模式信息来弥合领域的差距.
- 来自遥感图像的边缘特征增强了融合过程,并改善了零射击概括.
- 综合实验验证了该模型在 ZS-SBRSIR 任务上的有效性.
结论:
- 这种新型的交叉模式融合网络显著提升了ZS-SBRSIR的能力.
- 利用易于获取的多模式数据,如边缘特征和语义标签,是克服ZS-SBRSIR挑战的关键.
- 该方法证明了在遥感中基于素描的检索的性能和概括性得到了改进.
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