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BeadNet: deep learning-based bead detection and counting in low-resolution microscopy images
MOTIVATION: An automated counting of beads is required for many high-throughput experiments such as studying mimicked bacterial invasion processes. However, state-of-the-art algorithms under- or overestimate the number of beads in low-resolution images. In addition, expert knowledge is needed to adj...
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| Pubblicato in: | Bioinformatics |
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| Autori principali: | , , , , , , , |
| Natura: | Artigo |
| Lingua: | Inglês |
| Pubblicazione: |
Oxford University Press
2020
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| Soggetti: | |
| Accesso online: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7750944/ https://ncbi.nlm.nih.gov/pubmed/32589734 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1093/bioinformatics/btaa594 |
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