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cs.CV2026
SWITi: Quantifying and Reducing Tiling Artifacts with Sliding Window Inner Tiling
Federico Carrara, Aman Kukde, Melisande Croft +2
SWITi is a test-time method for reducing artifacts in tiled predictions, particularly for neural networks that learn posterior distributions from which solutions are sampled at inf…
cs.CV2026
ResMatching: Noise-Resilient Computational Super-Resolution via Guided Conditional Flow Matching
Anirban Ray, Vera Galinova, Florian Jug
Computational Super-Resolution (CSR) in fluorescence microscopy has, despite being an ill-posed problem, a long history. At its very core, CSR is about finding a prior that can be…
cs.CV2025
ε-Seg: Sparsely Supervised Semantic Segmentation of Microscopy Data
Sheida Rahnamai Kordasiabi, Damian Dalle Nogare, Florian Jug
Semantic segmentation of electron microscopy (EM) images of biological samples remains a challenge in the life sciences. EM data captures details of biological structures, sometime…