APA (7th ed.) Citation

Lu, S., Ye, J., An, F., & Zhang, Z. (2026). A Privacy-Preserving Classification Framework for Multi-Class Imbalanced Data Using Geometric Oversampling and Homomorphic Encryption. Applied Sciences (2076-3417), 16(3), 1283. https://doi.org/10.3390/app16031283

Chicago Style (17th ed.) Citation

Lu, Shoulei, Jun Ye, Fanglin An, and Zhengqi Zhang. "A Privacy-Preserving Classification Framework for Multi-Class Imbalanced Data Using Geometric Oversampling and Homomorphic Encryption." Applied Sciences (2076-3417) 16, no. 3 (2026): 1283. https://doi.org/10.3390/app16031283.

MLA (9th ed.) Citation

Lu, Shoulei, et al. "A Privacy-Preserving Classification Framework for Multi-Class Imbalanced Data Using Geometric Oversampling and Homomorphic Encryption." Applied Sciences (2076-3417), vol. 16, no. 3, 2026, p. 1283, https://doi.org/10.3390/app16031283.