APA (7th ed.) Citation

J, L., M, Z., Q, D., S, L., & S, P. (2026). MCM-UNet++: A Hybrid Soft Computing Framework for Multi-Scale Polyp Segmentation via Enhanced Global Context and Adaptive Feature Fusion. Sensors (Basel, Switzerland), 26(11), . https://doi.org/10.3390/s26113380

Chicago Style (17th ed.) Citation

J, Li, Zhao M, Du Q, Lu S, and Peng S. "MCM-UNet++: A Hybrid Soft Computing Framework for Multi-Scale Polyp Segmentation via Enhanced Global Context and Adaptive Feature Fusion." Sensors (Basel, Switzerland) 26, no. 11 (2026). https://doi.org/10.3390/s26113380.

MLA (9th ed.) Citation

J, Li, et al. "MCM-UNet++: A Hybrid Soft Computing Framework for Multi-Scale Polyp Segmentation via Enhanced Global Context and Adaptive Feature Fusion." Sensors (Basel, Switzerland), vol. 26, no. 11, 2026, https://doi.org/10.3390/s26113380.