Point Clouds Classification of Large Scenes based on Blueprint Separation Convolutional Neural Network
Author:
Affiliation:
1. Hangzhou Normal University,School of Information Science and Technology,Hangzhou,China
2. Zhejiang University of Technology,College of Computer Science and Technology,Hangzhou,China
Funder
Natural Science Foundation of Zhejiang Province
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9775971/9776016/09776241.pdf?arnumber=9776241
Reference23 articles.
1. Airborne LiDAR point cloud classification with global-local graph attention convolution neural network
2. Adaptive Hierarchical Down-Sampling for Point Cloud Classification;nezhadarya,2019
3. LU-Net: An Efficient Network for 3D LiDAR Point Cloud Semantic Segmentation Based on End-to-End-Learned 3D Features and U-Net
4. Research on point cloud classification based on deep learning[D];li;North University of China J,2020
5. Nonassociative Markov networks for 3D point cloud classification;shapovalov;Proc ISPRS Commission III Symp (PCV),2010
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1. BICANet: LiDAR Point Cloud Classification Network Based on Coordinate Attention and Blueprint Separation Involution Neural Network;IEEE Sensors Journal;2023-11-15
2. LiDAR Point Cloud Classification with Coordinate Attention Blueprint Separation Involution Neural Network;2023 26th International Conference on Computer Supported Cooperative Work in Design (CSCWD);2023-05-24
3. MFTR-Net: A Multi-Level Features Network with Targeted Regularization for Large-Scale Point Cloud Classification;Sensors;2023-04-10
4. Large Scale Point Cloud Classification Base on Graph-MLP++;2022 IEEE 9th International Conference on Data Science and Advanced Analytics (DSAA);2022-10-13
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