CaMeL-Net: Centroid-aware metric learning for efficient multi-class cancer classification in pathology images.
Computer methods and programs in biomedicine(2023)
摘要
The experimental results demonstrate that the prediction results by the proposed network are both accurate and reliable. The proposed network not only outperformed other related methods in cancer classification but also achieved superior computational efficiency during training and inference. The future study will entail further development of the proposed method and the application of the method to other problems and domains.
更多查看译文
关键词
Cancer grading,Deep metric learning,Computational pathology,Model efficiency
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要