融合注意力机制Mask RCNN的桥小脑角区听神经瘤和脑膜瘤的识别研究
胡小洋1,2,刘颖1,*(
),陈淑2,董彬彬3
),陈淑2,董彬彬3
Fusing Attention Mechanism with Mask RCNN for Recognition of Acoustic Neuroma and Meningioma in Cerebellopontine Angle
HU Xiaoyang1,2,LIU Ying1,*(),CHEN Shu2,DONG Binbin3
),CHEN Shu2,DONG Binbin3
图7. 5种模型验证集的loss曲线和mAP曲线.各模型的loss曲线都收敛良好，VGG19-CBAM的mAP曲线稳定性和精度最优
Fig. 7. Loss curves and mAP curves of 5 models in validation set. The loss curves of each model converge well, and the stability and accuracy of the mAP curve of VGG19-CBAM are optimal
