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Classification method for imbalanced LiDAR point cloud based on stack autoencoder
Peng Ren,
Qunli Xia
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Corresponding author for this work
School of Aerospace Engineering
Beijing Institute of Technology
Southwest Institute of Technical Physics
Research output
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Contribution to journal
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Article
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peer-review
3
Citations (Scopus)
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Computer Science
Autoencoder
100%
Automatic Generation
20%
Big Data
20%
Classification Method
100%
Classification Problem
20%
classification result
20%
Classifier
20%
Computational Complexity
20%
Data Classification
20%
Feature Construction
20%
Network Structures
20%
Point Cloud
100%
Training Data
20%
True Positive Rate
20%
Mathematics
Characteristic Distribution
33%
Classification Method
100%
Feature Construction
33%
Input Layer
33%
Positive Rate
33%
Physics
Big Data
100%