ArticleMethods in molecular biology (Clifton, N.J.)2026
Deep Learning Tools for Single Quantum Dot Tracking.
Article in Methods in molecular biology (Clifton, N.J.), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Deep learning, a powerful and widely effective subset of machine learning, offers a promising foundation for developing an automatic, parameter-free analysis pipelines that replace conventional, multistep workflows for single quantum dot tracking. This chapter provides detailed protocols for installing and implementing open-source, state-of-the-art deep learning tools to detect individual quantum dots in time-lapse image series and reconstruct their trajectories. Additionally, it includes practical guidelines for troubleshooting common errors encountered when deploying these tools for single quantum dot tracking.
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