Self-contrastive learning enables interference-resilient and generalizable fluorescence microscopy signal detection without interference modeling
Fengdi Zhang, Ruqi Huang, Meiqian Xin, Haoran Meng, Danheng Gao, Ying Fu, Juntao Tony Gao, Xiangyang Ji
This paper introduces DEPAF, a self-contrastive learning method for fluorescence microscopy signal detection that is interference-resilient and generalizable without requiring interference modeling.
bioRxiv · Apr 8, 2025 · PreprintBioinformatics