APA (7th ed.) Citation

Hendria, W. F., Kim, H., & Seo, D. (2025). Multi-model anomaly detection for industrial inspection with dynamic loss weighting and soft-hard features loss. Neural Computing & Applications, 37(21), 17031. https://doi.org/10.1007/s00521-025-11367-3

Chicago Style (17th ed.) Citation

Hendria, Willy Fitra, Hanbi Kim, and Daeho Seo. "Multi-model Anomaly Detection for Industrial Inspection with Dynamic Loss Weighting and Soft-hard Features Loss." Neural Computing & Applications 37, no. 21 (2025): 17031. https://doi.org/10.1007/s00521-025-11367-3.

MLA (9th ed.) Citation

Hendria, Willy Fitra, et al. "Multi-model Anomaly Detection for Industrial Inspection with Dynamic Loss Weighting and Soft-hard Features Loss." Neural Computing & Applications, vol. 37, no. 21, 2025, p. 17031, https://doi.org/10.1007/s00521-025-11367-3.