Cargando…
Deep Learning for Flow Sculpting: Insights into Efficient Learning using Scientific Simulation Data
A new technique for shaping microfluid flow, known as flow sculpting, offers an unprecedented level of passive fluid flow control, with potential breakthrough applications in advancing manufacturing, biology, and chemistry research at the microscale. However, efficiently solving the inverse problem...
Autores principales: | Stoecklein, Daniel, Lore, Kin Gwn, Davies, Michael, Sarkar, Soumik, Ganapathysubramanian, Baskar |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group
2017
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5389406/ https://www.ncbi.nlm.nih.gov/pubmed/28402332 http://dx.doi.org/10.1038/srep46368 |
Ejemplares similares
-
Crop yield prediction integrating genotype and weather variables using deep learning
por: Shook, Johnathon, et al.
Publicado: (2021) -
A deep learning framework to discern and count microscopic nematode eggs
por: Akintayo, Adedotun, et al.
Publicado: (2018) -
Plant disease identification using explainable 3D deep learning on hyperspectral images
por: Nagasubramanian, Koushik, et al.
Publicado: (2019) -
Machine Learning Approach for Prescriptive Plant Breeding
por: Parmley, Kyle A., et al.
Publicado: (2019) -
Deep learning-based phenotyping for genome wide association studies of sudden death syndrome in soybean
por: Rairdin, Ashlyn, et al.
Publicado: (2022)