Promising Hyperparameter Configurations for Deep Fully Connected Neural Networks to Improve Image Reconstruction in Proton Radiotherapy is a research paper published in 2021 IEEE International Conference on Big Data (Big Data) (2021). On theSindex it has a DataRank of 0. It has been cited 5 times.
Scored on demand from live citation data
DataRank reads this dataset's downstream impact straight off the citation graph β no black box, no proprietary weighting. How is this computed?
FAIR checklist signals are shown for context only and do not affect DataRank scoring.
We only score data papers we can read in full β never from an abstract alone.
National Science Foundation
Grant: 1726023
MRI: Acquisition of Cutting-Edge GPU and Phi Nodes for the Interdisciplinary UMBC High Performance Computing Facility
National Science Foundation
Grant: 2050943
REU Site: Online Interdisciplinary Big Data Analytics in Science and Engineering
National Science Foundation
Grant: 1228778
MRI: Acquisition of Hybrid CPU/GPU Nodes for the Interdisciplinary UMBC High Performance Computing Facility
National Science Foundation
Grant: 0821311
SCREMS: Parallel Computing for Interdisciplinary Research in Mathematics and Statistics
National Science Foundation
Grant: 0821258
MRI: Acquisition of an Interdisciplinary Facility for High-Performance Computing
National Institutes of Health
Grant: 5R01CA187416-03
Prompt Gamma Imaging for the in-vivo range verification during proton radiotherapy
Fields of Study