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西北工业大学 国内
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Terrain classification of aerial image based on low-rank recovery and sparse representation
Xu Ma, Shuai Hao,
Yongmei Cheng
自动化学院
Xi'an University of Science and Technology
科研成果
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探究 'Terrain classification of aerial image based on low-rank recovery and sparse representation' 的科研主题。它们共同构成独一无二的指纹。
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Computer Science
Sparse Representation
100%
Unmanned Aerial Vehicle
66%
image feature
66%
Experimental Result
33%
Image Classification
33%
Classification Method
33%
Classification Accuracy
33%
Texture Feature
33%
Image Database
33%
Lagrange Multiplier Method
33%
Illumination Variation
33%
Engineering
Aerial Image
100%
Unmanned Aerial Vehicle
66%
Experimental Result
33%
Image Classification
33%
Test Sample
33%
Texture Feature
33%
Classification Accuracy
33%
Classification Method
33%
Lagrange Multiplier Method
33%
Illumination Variation
33%
Earth and Planetary Sciences
Pilotless Aircraft
100%
Image Classification
100%