Pap Gergely and Grósz Tamás and Tóth László: Semi-supervised training of cell-classifier neural networks.
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Abstract
Nowadays, microscopes used in biological research produce a huge amount of image data. Manually processing the images is a very time-consuming and resource-heavy task, so the development and implementation of new automatic systems is required. Moreover, as we have access to a large amount of unlabeled data, while labels are only available for a small subset, these novel methods should be able to process large amounts of unlabeled data with minimal manual supervision. Here, we apply neural networks to classify cells present in biological images, and show that their accuracy can be improved by using semi-supervised training algorithms.
| Item Type: | Conference or Workshop Item |
|---|---|
| Journal or Publication Title: | Conference of PhD Students in Computer Science |
| Date: | 2018 |
| Volume: | 11 |
| Page Range: | pp. 84-87 |
| Event Title: | Conference of PhD students in computer science (11.) (2018) (Szeged) |
| Related URLs: | http://acta.bibl.u-szeged.hu/59477/ |
| Uncontrolled Keywords: | Számítástechnika, Biológiai kutatás |
| Additional Information: | Bibliogr.: 87. p. ; összefoglalás angol nyelven |
| Date Deposited: | 2019. Nov. 04. 09:53 |
| Last Modified: | 2022. Nov. 08. 10:18 |
| URI: | http://acta.bibl.u-szeged.hu/id/eprint/61772 |
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