- Title Information
- Title
- Data from "Automated identification of multinucleated germ cells with U-Net"
- Abstract
- This data set contains 1) best fit model for trained MNG prediction U-Net 2) best fit model parameters for trained MNG prediction U-Net 3) the full record of the cropped images used in training the model 4) the final output neural nets 5) additional files needed for running the code and 6) stitched output files.
- Name
- Name Part
- Bell, Samuel
- Role
- Role Term (marcrelator)
(authorityURI="http://id.loc.gov/vocabulary/relators", valueURI="http://id.loc.gov/vocabulary/relators/cre")
- Creator
- Name
- Name Part
- Spade, Daniel
- Role
- Role Term (marcrelator)
(authorityURI="http://id.loc.gov/vocabulary/relators", valueURI="http://id.loc.gov/vocabulary/relators/cre")
- Creator
- Name
- Name Part
- Zsom, Andras
- Role
- Role Term (marcrelator)
(authorityURI="http://id.loc.gov/vocabulary/relators", valueURI="http://id.loc.gov/vocabulary/relators/cre")
- Creator
- Origin Information
- Date Created
- 2020
- Subject (Local)
- Topic
- u-net
- Subject (Local)
- Topic
- neural network
- Subject (Local)
- Topic
- cell
- Subject (Local)
- Topic
- MNG
- Subject (Local)
- Topic
- Multinucleated germ cells
- Type of Resource
- software, multimedia
- Genre
- data set
- Access Condition:
use and reproduction
(href="https://creativecommons.org/licenses/by-nc-sa/4.0/")
-
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International license
- Access Condition:
logo
(href="https://licensebuttons.net/l/by-nc-sa/4.0/88x31.png")
- Note:
funding
-
This research is supported by the Institute of Environmental Health Sciences (NIEHS) of the National Institutes of Health (NIH) under award R00 ES025231
- Identifier:
DOI
- 10.26300/rv2a-kp40