Manifold coordinate representations of hyperspectral imagery: Improvements in algorithm performance and computational efficiency
暂无分享,去创建一个
[1] Charles M. Bachmann,et al. A credit assignment approach to fusing classifiers of multiseason hyperspectral imagery , 2003, IEEE Trans. Geosci. Remote. Sens..
[2] Charles M. Bachmann. Improving the performance of classifiers in high-dimensional remote sensing applications: an adaptive resampling strategy for error-prone exemplars (ARESEPE) , 2003, IEEE Trans. Geosci. Remote. Sens..
[3] Thomas L. Ainsworth,et al. A scalable approach to modeling nonlinear structure in hyperspectral imagery and other high-dimensional data using manifold coordinate representations , 2010, Defense + Commercial Sensing.
[4] Thomas L. Ainsworth,et al. Automated Estimation of Spectral Neighborhood Size in Manifold Coordinate Representations of Hyperspectral Imagery: Implications for Anomaly Finding, Bathymetry Retrieval, and Land Applications , 2008, IGARSS 2008 - 2008 IEEE International Geoscience and Remote Sensing Symposium.
[5] Thomas L. Ainsworth,et al. Local intrinsic dimensionality of hyperspectral imagery from non-linear manifold coordinates , 2007, 2007 IEEE International Geoscience and Remote Sensing Symposium.
[6] Thomas L. Ainsworth,et al. Exploiting manifold geometry in hyperspectral imagery , 2005, IEEE Transactions on Geoscience and Remote Sensing.
[7] Thomas L. Ainsworth,et al. Bathymetric Retrieval From Hyperspectral Imagery Using Manifold Coordinate Representations , 2009, IEEE Transactions on Geoscience and Remote Sensing.
[8] Thomas L. Ainsworth,et al. Improved manifold coordinate representations of hyperspectral imagery , 2005, Proceedings. 2005 IEEE International Geoscience and Remote Sensing Symposium, 2005. IGARSS '05..