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Benchmarking the Cell Image Segmentation Models Robustness under the Microscope Optical Aberrations
Overall, this research aims to guide researchers in effectively utilizing cell segmentation models in the presence of minor optical aberrations.
Ammonia-Net: A Multi-task Joint Learning Model for Multi-class Segmentation and Classification in Tooth-marked Tongue Diagnosis
After a number of extensive experiments, the experimental results show that the proposed model achieves 99. 06% accuracy in the two-class classification task of tooth-marked tongue identification and 80. 02%.
GAME: Generalized deep learning model towards multimodal data integration for early screening of adolescent mental disorders
The timely identification of mental disorders in adolescents is a global public health challenge. Single factor is difficult to detect the abnormality due to its complex and subtle nature.
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