Ammonia-Net: A Multi-task Joint Learning Model for Multi-class Segmentation and Classification in Tooth-marked Tongue Diagnosis.
Shunkai ShiYuqi WangQihui YeYanran WangYiming ZhuMuhammad HassanMelliou AikateriniDongmei YuPublished in: CoRR (2023)
Keyphrases
- multi class
- multi task
- multi task learning
- learning tasks
- multi class classifier
- feature selection
- multi class classification
- support vector machine
- supervised learning
- probabilistic model
- prior knowledge
- multiple classes
- gaussian processes
- unsupervised learning
- classification models
- data sets
- error correcting output codes
- feature extraction
- multi class boosting
- learning models
- support vector
- theoretical analysis
- model selection
- multitask learning
- binary classifiers
- kernel machines
- binary and multi class
- learning problems
- text categorization
- image classification
- semi supervised
- classification accuracy
- reinforcement learning
- image segmentation
- data mining