Cargando…
Fast deep neural correspondence for tracking and identifying neurons in C. elegans using semi-synthetic training
We present an automated method to track and identify neurons in C. elegans, called ‘fast Deep Neural Correspondence’ or fDNC, based on the transformer network architecture. The model is trained once on empirically derived semi-synthetic data and then predicts neural correspondence across held-out re...
| Autores principales: | , , , , , |
|---|---|
| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
eLife Sciences Publications, Ltd
2021
|
| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8367385/ https://www.ncbi.nlm.nih.gov/pubmed/34259623 http://dx.doi.org/10.7554/eLife.66410 |