A transfer learning-based network model integrating kernel convolution with graph attention mechanism for point cloud segmentation of livestock-Reference-Cited by-同舟云学术

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A transfer learning-based network model integrating kernel convolution with graph attention mechanism for point cloud segmentation of livestock

Published:2024-10 Issue: Volume:225 Page:109325
ISSN:0168-1699
Container-title:Computers and Electronics in Agriculture
language:en
Short-container-title:Computers and Electronics in Agriculture

Author:

Yuanyuan Shi,Yuxiao Wang,Ling Yin,Zhenfang Wu,Junyong Lin,Xuhong Tian,Qiong Huang,Sumin Zhang,Zhiying Li

Funder

Special Project for Research and Development in Key areas of Guangdong Province

Guangzhou Key Laboratory of Multilingual Intelligent Processing

National Pesticide Engineering Research Center, Nankai University

National Natural Science Foundation of China

National Aerospace Science Foundation of China

Publisher

Elsevier BV

Reference43 articles.

1. Akwensi, P., Wang, R., 2022. Attention-Based multi-scale graph convolution for point cloud semantic segmentation. IEEE International Geoscience and Remote Sensing Symposium (pp.7515-7518). doi: 10.1109/IGARSS46834.2022.9884247.

2. Anvekar, T., Bazaian, D., 2023. GPr-Net: Geometric prototypical network for point cloud few-shot learning.In: Proceedings of the IEEE conference on computer vision and pattern recognition (pp. 4178-4187).

3. A local-global feature fusing method for point clouds semantic segmentation;Bi;IEEE Access,2023

4. Generative and discriminative voxel modeling with convolutional neural networks;Brock;arXiv:1608.04236,2016

5. Chen, X., Ma, H., Wan, J., Li, B., Xia, T., 2017. Multi-view 3D object detection network for autonomous driving. In: Proceedings of the IEEE conference on computer vision and pattern recognition, arXiv:1611.07759. doi: 10.48550/arXiv.1611.07759.

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