Article Versions Notes

Seo H, Lee S, Yun S, Leem S, So S, Han DH. RenseNet: A Deep Learning Network Incorporating Residual and Dense Blocks with Edge Conservative Module to Improve Small-Lesion Classification and Model Interpretation. Cancers. 2024; 16(3):570. https://doi.org/10.3390/cancers16030570

Seo, Hyunseok, Seokjun Lee, Sojin Yun, Saebom Leem, Seohee So, and Deok Hyun Han. 2024. "RenseNet: A Deep Learning Network Incorporating Residual and Dense Blocks with Edge Conservative Module to Improve Small-Lesion Classification and Model Interpretation" Cancers 16, no. 3: 570. https://doi.org/10.3390/cancers16030570

Seo, H., Lee, S., Yun, S., Leem, S., So, S., & Han, D. H. (2024). RenseNet: A Deep Learning Network Incorporating Residual and Dense Blocks with Edge Conservative Module to Improve Small-Lesion Classification and Model Interpretation. Cancers, 16(3), 570. https://doi.org/10.3390/cancers16030570