公开(公告)号：US11710307B2

公开(公告)日：2023-07-25

申请号：US17168580

申请日：2021-02-05

申请人： Central South University

发明人： Chao Tao ,  Weipeng Lu ,  Ji Qi ,  Haifeng Li

IPC分类号： G06V20/10 ,  G06N3/04 ,  G06N3/08 ,  G06F18/21 ,  G06F18/2134 ,  G06V10/75 ,  G06V10/77 ,  G06V10/776 ,  G06V10/80 ,  G06V10/32 ,  G06V20/13

CPC分类号： G06V20/176 ,  G06F18/217 ,  G06F18/2134 ,  G06N3/04 ,  G06N3/08 ,  G06V10/32 ,  G06V10/7515 ,  G06V10/776 ,  G06V10/7715 ,  G06V10/806 ,  G06V20/13

摘要： An urban remote sensing image scene classification method in consideration of spatial relationships is provided and includes following steps of: cutting a remote sensing image into sub-images in an even and non-overlapping manner; performing a visual information coding on each of the sub-images to obtain a feature image Fv; inputting the feature image Fv into a crossing transfer unit to obtain hierarchical spatial characteristics; performing convolution of dimensionality reduction on the hierarchical spatial characteristics to obtain dimensionality-reduced hierarchical spatial characteristics; and performing a softmax model based classification on the dimensionality-reduced hierarchical spatial characteristics to obtain a classification result. The method comprehensively considers the role of two kinds of spatial relationships being regional spatial relationship and long-range spatial relationship in classification, and designs three paths in a crossing transfer unit for relationships fusion, thereby obtaining a better urban remote sensing image scene classification result.

公开(公告)号：US20210264150A1

公开(公告)日：2021-08-26

申请号：US17168580

申请日：2021-02-05

申请人： Central South University

发明人： Chao Tao ,  Weipeng Lu ,  Ji Qi ,  Haifeng Li

IPC分类号： G06K9/00 ,  G06K9/62 ,  G06N3/04 ,  G06N3/08

摘要： An urban remote sensing image scene classification method in consideration of spatial relationships is provided and includes following steps of: cutting a remote sensing image into sub-images in an even and non-overlapping manner; performing a visual information coding on each of the sub-images to obtain a feature image Fv; inputting the feature image Fv into a crossing transfer unit to obtain hierarchical spatial characteristics; performing convolution of dimensionality reduction on the hierarchical spatial characteristics to obtain dimensionality-reduced hierarchical spatial characteristics; and performing a softmax model based classification on the dimensionality-reduced hierarchical spatial characteristics to obtain a classification result. The method comprehensively considers the role of two kinds of spatial relationships being regional spatial relationship and long-range spatial relationship in classification, and designs three paths in a crossing transfer unit for relationships fusion, thereby obtaining a better urban remote sensing image scene classification result.