Training Neural Networks to Approach the Optimum Bayes Estimator in Dense Multi-Emitter Localization (arxiv.org)
arXiv:2609.20465v1 Announce Type: new
Abstract: We train neural networks on synthesized frames to approach the optimum Bayes estimator for dense emitter localization. The result justifies the future work on training neural networks to achieve high-throughput large-FOV super spatiotemporal resolution SMLM.
Abstract: We train neural networks on synthesized frames to approach the optimum Bayes estimator for dense emitter localization. The result justifies the future work on training neural networks to achieve high-throughput large-FOV super spatiotemporal resolution SMLM.
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