Boundary-Aware Fine-Tuning of SAM2 for Seismic Facies Segmentation using Multi-Loss Optimization

References

1. Amid, E., Warmuth, M. K., Anil, R., and Koren, T. [2019] Robust Bi-Tempered Logistic Loss Based on Bregman Divergences. arXiv.Org. https://arxiv.org/abs/1906.03361
   [Google Scholar]
2. Ghosh, A. [2025] Finetuning SAM2 for leaf disease segmentation – tutorial. LearnOpenCV. https://learnopencv.com/finetuning-sam2/
   [Google Scholar]
3. Hong, Y., Zhou, X., Hua, R., Lv, Q., and Dong, J. [2024] Watersam: Adapting Sam for underwater object segmentation. MDPI, 12, 9, 1616. https://www.mdpi.com/2077-1312/12/9/1616
   [Google Scholar]
4. Leu, J., Tong, Z., Doty, A., Tsimpoukis, S., and Yang, J. [2024] Machine Learning-Aided Spatial Adaptation for Improved Digital Image Correlation Analysis of Complex Geometries. doi:10.21203/rs.3.rs‑5566473/v1
   https://doi.org/10.21203/rs.3.rs-5566473/v1 [Google Scholar]
5. Lomask, Jesse, Clapp, Robert G. and Biondi, Biondo, (2007), “Application of image segmentation to tracking 3D salt boundaries,” GEOPHYSICS72: P47–P56.
   [Google Scholar]
6. Minh Ôn VûNgoc, YiziChen, NicolasBoutry, JosephChazalon, EdwinCarlinet, et al.. [2021] Introducing the Boundary-Aware loss for deep image segmentation. British Machine Vision Conference (BMVC)2021, Nov 2021, Virtual, United Kingdom. ffhal-03417244
   [Google Scholar]
7. Ravi, N., Gabeur, V., Hu, Y.-T., Hu, R., Ryali, C., Ma, T., Khedr, H., Rädle, R., Rolland, C., Gustafson, L., Mintun, E., Pan, J., Alwala, K. V., Carion, N., Wu, C.-Y., Girshick, R., Dollár, P., and Feichtenhofer, C. [2024] SAM 2: Segment Anything in Images and Videos. arXiv.Org. https://doi.org/10.48550/arXiv.2408.00714
   [Google Scholar]
8. Yao, Y., Yang, Q., Cui, M., and Bo, L. [2025] Towards Fine-Grained Interactive Segmentation in Images and Videos. arXiv.Org. https://arxiv.org/abs/2502.09660
   [Google Scholar]
9. Yeung, M., Sala, E., Schönlieb, C.-B., and Rundo, L. [2022] Unified Focal Loss: Generalizing Dice and Cross Entropy-Based Losses to Handle Class Imbalanced Medical Image Segmentation. Computerized Medical Imaging and Graphics, 95, 102026. doi:10.1016/j.compmedimag.2021.102026
   https://doi.org/10.1016/j.compmedimag.2021.102026 [Google Scholar]