通过双向mamba和域混合网络进行跨场景的高光谱图像分类
IEEE transactions on neural networks and learning systems
|January 13, 2026
概括
本研究介绍了双向mamba和域混合网络 (BMDMnet),以解决超光谱图像 (HSI) 分类中的域转移问题. 这种新型网络有效地捕捉了远程依赖关系,并减轻了域间隙,以提高HSI分类准确性.
科学领域:
- 遥感 遥感 遥感 遥感
- 计算机视觉 计算机视觉
- 机器学习 机器学习
背景情况:
- 域移动在超光谱图像 (HSI) 分类中是一个重大挑战.
- 现有的域调整 (DA) 方法通过专注于特征空间对齐来应对大型域转移.
- 将不同的源域和目标域映射到一个共享的功能空间仍然很困难.
研究的目的:
- 开发一种有效的方法,用于域变化下的高光谱图像分类.
- 提出一种新的网络架构,能够有效地捕获本地和全球特征.
- 引入域混合策略,以弥合源域和目标域之间的差距.
主要方法:
- 建议采用双向mamba模块 (BMM) 进行高效的远程依赖捕获,解决CNN和变压器的局限性.
- 采用自蒸策略,使用稳定的教师模型进行可靠的目标领域预测.
- 一个域混合监督学习 (DMSL) 模块创建了一个混合域,以减少数据空间中的域间差距.
主要成果:
- 拟议的BMDMnet与最先进的算法相比显示出更高的性能.
- 在三个跨场景数据集中进行了实验,验证了该方法的有效性.
- 整合BMM和DMSL显著提高了域移动下的HSI分类准确性.
结论:
- 该BMDMnet提供了一个高效和有效的解决方案,用于高光谱图像分类与域转移.
- 拟议的BMM和DMSL模块成功地解决了现有的域调整技术的局限性.
- 这项工作通过提供一个强大的方法来处理域变异性来推动HSI分类领域的发展.
相关概念视频
01:22Force Classification
2.3K
Forces play a crucial role in the study of physics and engineering. They are essential in describing the motion, behavior, and equilibrium of objects in the physical world. Forces can be classified based on their origin, type, and direction of action.
Contact and non-contact forces are two of the most widely used categories of forces. As the name suggests, contact forces require physical contact between two objects to act upon each other. Examples of contact forces include frictional,...
Contact and non-contact forces are two of the most widely used categories of forces. As the name suggests, contact forces require physical contact between two objects to act upon each other. Examples of contact forces include frictional,...
2.3K
01:29Aggregates Classification
964
Aggregate classification is generally based on its size, petrographic characteristics, weight, and source. Size classification ranges from coarse to fine aggregates, defined by the size of the particles. Coarse aggregates are particles that do not pass through ASTM sieve No. 4, and aggregates that pass through the sieve are fine aggregates.
Petrographic classification groups aggregates based on common mineralogical characteristics. Some of the common mineral groups found in aggregates are...
Petrographic classification groups aggregates based on common mineralogical characteristics. Some of the common mineral groups found in aggregates are...
964