MPCNet: Improved MeshSegNet Based on Position Encoding and Channel Attention
In the process of orthodontic treatment, it is a very important step to accurately segment each tooth and jaw model with computer assistance. The use of deep learning technology methods for tooth segmentation can not only save a lot of manual interaction and time cost but also improve the treatment...
Saved in:
| Main Authors: | Hanqing Hu, Zhengxun Li, Weichao Gao |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
IEEE
2023-01-01
|
| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10063862/ |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
MambaMeshSeg-Net: A Large-Scale Urban Mesh Semantic Segmentation Method Using a State Space Model with a Hybrid Scanning Strategy
by: Wenjie Zi, et al.
Published: (2025-05-01) -
A point cloud segmentation network with hybrid convolution and differential channels
by: Xiaoyan Zhang, et al.
Published: (2025-04-01) -
MFSM-Net: Multimodal Feature Fusion for the Semantic Segmentation of Urban-Scale Textured 3D Meshes
by: Xinjie Hao, et al.
Published: (2025-04-01) -
Semi-MeshSeg: A semi-supervised semantic segmentation network for large-scale urban textured meshes using all pseudo-labels
by: Wenjie Zi, et al.
Published: (2025-08-01) -
SCRM-Net: Self-Supervised Deep Clustering Feature Representation for Urban 3D Mesh Semantic Segmentation
by: Jiahui Wang, et al.
Published: (2025-04-01)