NGM software for applied neurogoniometry

Name: NGM software for applied neurogoniometry
Creator: Oleg Gradov
License: https://creativecommons.org/licenses/by/4.0/

Citation Author(s):: Alexander Notchenko

Oleg Gradov
Submitted by:: Oleg Gradov
Last updated:: Wed, 01/16/2019 - 08:35
DOI:: 10.21227/r842-xt38

129 views

Categories:

Image Fusion
Biomedical and Health Sciences
Neuroscience
Medical Imaging
Biophysiological Signals
Brain

No Ratings Yet

ACCESS DATASET CITE SHARE/EMBED

Abstract

NGM software for applied neurogoniometry. See our previous articles.

Instructions:

NGM software for applied neurogoniometry. See our previous articles.

Dataset Files

NGM_v1.00.zip (Size: 13.18 KB)
NGM_v1.02.zip (Size: 12.4 KB)

QUESTIONS?

Send Author a Private Message
Report a problem with this Dataset

Upload your Dataset

How to Upload Dataset Files Directly to AWS

IEEE DataPort Subscribers may upload their dataset files directly to IEEE DataPort's AWS S3 file storage. Please read the Upload Your Files directly to the IEEE DataPort S3 Bucket help topic for detailed instructions.

You will need the following information to complete your upload:

Your AWS Access Key and Secret key, which can be found on your IEEE DataPort User Profile.
DATASET TYPE: data
USERID: 1353045
DATASETID: 14627

Dataset Access

How to access this dataset

This dataset requires an IEEE DataPort Subscription.

For all the IEEE Society Members, please login now to the IEEE DataPort platform to access your FREE IEEE DataPort Subscription.

Subscribe Now

Dataset Citation

Alexander Notchenko, Oleg Gradov , "NGM software for applied neurogoniometry", IEEE Dataport, January 16, 2019, doi:10.21227/r842-xt38

@data{r842-xt38-19,
doi = {10.21227/r842-xt38},
url = {https://dx.doi.org/10.21227/r842-xt38},
author = {Alexander Notchenko and Oleg Gradov },
publisher = {IEEE Dataport},
title = {NGM software for applied neurogoniometry},
year = {2019} }

TY - DATA
T1 - NGM software for applied neurogoniometry
AU - Alexander Notchenko; Oleg Gradov
PY - 2019
PB - IEEE Dataport
UR - 10.21227/r842-xt38
ER -

Alexander Notchenko, Oleg Gradov (2019). NGM software for applied neurogoniometry. IEEE Dataport. https://dx.doi.org/10.21227/r842-xt38

Alexander Notchenko, Oleg Gradov 2019 NGM software for applied neurogoniometry. Available at: https://dx.doi.org/10.21227/r842-xt38

Alexander Notchenko, Oleg Gradov .(2019). "NGM software for applied neurogoniometry." Web,

1. Alexander Notchenko, Oleg Gradov . NGM software for applied neurogoniometry [Internet]. IEEE Dataport; 2019. Available from: https://dx.doi.org/10.21227/r842-xt38

Alexander Notchenko, Oleg Gradov , "NGM software for applied neurogoniometry,", doi: 10.21227/r842-xt38.

Share / Embed

Embed this dataset on another website

Copy and paste the HTML code below to embed your dataset:

Share via email or social media

Click the buttons below:

Share a link to this dataset

Permalink: https://ieee-dataport.org//documents/ngm-software-applied-neurogoniometry

DOI Link: https://dx.doi.org/10.21227/r842-xt38

Datasets

Standard Dataset

NGM software for applied neurogoniometry

Abstract

Instructions:

Dataset Files

QUESTIONS?

More from this Author

Fern stem: detection of radial and circular pecularities using FFTW-based software

Cusurbits stem: detection of radial and circular pecularities using FFTW-based software

Tilia stem: detection of radial and circular pecularities using FFTW-based software

Honeysuckle flower: multiscale nervature detection using FFTW-based sofytware

Broad bean leaf epidermis: spectrozonal and multi-angle lens-less imaging and image processing

Epidermis of allium: FFTW-based regulometry case

Oral mucosa: digital photometric lens-less spectrozonal transmittance testing of thin slices or ultrathin histological sections.

Volvox sp. (Volvox L., 1758) Pfeffer's osmometry: FFTW-based LUCAS-like real time approach

More like this Dataset

FLAME 2: Fire detection and modeLing: Aerial Multi-spectral imagE dataset

SEN12-FLOOD : a SAR and Multispectral Dataset for Flood Detection

Paddy Doctor: A Visual Image Dataset for Automated Paddy Disease Classification and Benchmarking

2018 IEEE GRSS Data Fusion Challenge – Fusion of Multispectral LiDAR and Hyperspectral Data

Thermal Visual Paired Dataset

Azure Kinect 3D skeleton and foot pressure data for pathological gaits