Cite
MAC-ResNet: Knowledge Distillation Based Lightweight Multiscale-Attention-Crop-ResNet for Eyelid Tumors Detection and Classification.
MLA
Huang, Xingru, et al. “MAC-ResNet: Knowledge Distillation Based Lightweight Multiscale-Attention-Crop-ResNet for Eyelid Tumors Detection and Classification.” Journal of Personalized Medicine, vol. 13, no. 1, Jan. 2023, p. 89. EBSCOhost, https://doi.org/10.3390/jpm13010089.
APA
Huang, X., Yao, C., Xu, F., Chen, L., Wang, H., Chen, X., Ye, J., & Wang, Y. (2023). MAC-ResNet: Knowledge Distillation Based Lightweight Multiscale-Attention-Crop-ResNet for Eyelid Tumors Detection and Classification. Journal of Personalized Medicine, 13(1), 89. https://doi.org/10.3390/jpm13010089
Chicago
Huang, Xingru, Chunlei Yao, Feng Xu, Lingxiao Chen, Huaqiong Wang, Xiaodiao Chen, Juan Ye, and Yaqi Wang. 2023. “MAC-ResNet: Knowledge Distillation Based Lightweight Multiscale-Attention-Crop-ResNet for Eyelid Tumors Detection and Classification.” Journal of Personalized Medicine 13 (1): 89. doi:10.3390/jpm13010089.