SHPNeXt: A Novel Method of Multi-Scale and Variable Resolution AI-Based Tongue Image Segmentation
In the domain of Traditional Chinese Medicine, accurately segmenting tongue images is fundamental for computer-assisted diagnosis. Yet, current models often falter with images of diverse scales and clarity, impeding their widespread application. To address this challenge, we propose SHPNeXt, an inno...
Saved in:
| Main Authors: | Chong-Xiao Peng, Zhi-Jun Gao, Jin-Huan Wang, Xin Yue, Yi Li, Li-Li Sun, Yin-Huan Sun, Fu-Quan Du |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
IEEE
2025-01-01
|
| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10938541/ |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Tongue-LiteSAM: A Lightweight Model for Tongue Image Segmentation With Zero-Shot
by: Daiqing Tan, et al.
Published: (2025-01-01) -
Deep learning-based automated tongue analysis system for assisted Chinese medicine diagnosis
by: Tingnan Chen, et al.
Published: (2025-04-01) -
ESSegNeXt: A Novel Building Extraction Framework Based on Generalized SamGeo and SegNeXt Models Using High-Resolution Remote Sensing Images
by: Qi Lu, et al.
Published: (2025-01-01) -
Morphological Analysis and Subtype Detection of Acute Myeloid Leukemia in High-Resolution Blood Smears Using ConvNeXT
by: Mubarak Taiwo Mustapha, et al.
Published: (2025-02-01) -
CMPF-UNet: a ConvNeXt multi-scale pyramid fusion U-shaped network for multi-category segmentation of remote sensing images
by: Ning Li, et al.
Published: (2024-01-01)