Towards on-board hyperspectral satellite image segmentation: Understanding robustness of deep learning through simulating acquisition conditions
Although hyperspectral images capture very detailed information about the scanned objects,
their efficient analysis, transfer, and storage are still important practical challenges due to …
their efficient analysis, transfer, and storage are still important practical challenges due to …
Deep ensembles for hyperspectral image data classification and unmixing
Hyperspectral images capture very detailed information about scanned objects and, hence,
can be used to uncover various characteristics of the materials present in the analyzed …
can be used to uncover various characteristics of the materials present in the analyzed …
Unbiased Validation of Hyperspectral Unmixing Algorithms
Hyperspectral unmixing is one of the most challenging tasks in the analysis of such data.
There have been an array of algorithms proposed for this problem so far, but they are …
There have been an array of algorithms proposed for this problem so far, but they are …