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Multicluster Spatial-Spectral Unsupervised Feature Selection for Hyperspectral Image Classification.

, , , , and . IEEE Geosci. Remote. Sens. Lett., 12 (8): 1660-1664 (2015)

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Efficient Multiple Feature Fusion With Hashing for Hyperspectral Imagery Classification: A Comparative Study., , , , , and . IEEE Trans. Geosci. Remote. Sens., 54 (8): 4461-4478 (2016)Train in Dense and Test in Sparse: A Method for Sparse Object Detection in Aerial Images., , , , , and . IEEE Geosci. Remote. Sens. Lett., (2022)Multicluster Spatial-Spectral Unsupervised Feature Selection for Hyperspectral Image Classification., , , , and . IEEE Geosci. Remote. Sens. Lett., 12 (8): 1660-1664 (2015)Improving tumor co-segmentation on PET-CT images with 3D co-matting., , , , , , and . ISBI, page 224-227. IEEE, (2018)Discriminant Tensor Spectral-Spatial Feature Extraction for Hyperspectral Image Classification., , , , , , and . IEEE Geosci. Remote. Sens. Lett., 12 (5): 1028-1032 (2015)3D Alpha Matting Based Co-segmentation of Tumors on PET-CT Images., , , and . CMMI/RAMBO/SWITCH@MICCAI, volume 10555 of Lecture Notes in Computer Science, page 31-42. Springer, (2017)Sparse Hierarchical Clustering for VHR Image Change Detection., , , , and . IEEE Geosci. Remote Sensing Lett., 12 (3): 577-581 (2015)Multi-scale segmentation using deep graph cuts: Robust lung tumor delineation in MVCBCT., , , and . ISBI, page 514-518. IEEE, (2018)3D fully convolutional networks for co-segmentation of tumors on PET-CT images., , , , , , and . ISBI, page 228-231. IEEE, (2018)3-D Surface Segmentation Meets Conditional Random Fields., , , and . CoRR, (2019)