Science Score: 23.0%
This score indicates how likely this project is to be science-related based on various indicators:
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○CITATION.cff file
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○codemeta.json file
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○.zenodo.json file
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✓DOI references
Found 6 DOI reference(s) in README -
✓Academic publication links
Links to: frontiersin.org, acm.org, zenodo.org -
○Academic email domains
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○Institutional organization owner
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○JOSS paper metadata
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○Scientific vocabulary similarity
Low similarity (14.4%) to scientific vocabulary
Keywords
Repository
Social Signal Processing for Android
Basic Info
- Host: GitHub
- Owner: hcmlab
- License: gpl-3.0
- Language: Java
- Default Branch: master
- Homepage: https://hcmlab.github.io/ssj
- Size: 325 MB
Statistics
- Stars: 32
- Watchers: 5
- Forks: 12
- Open Issues: 1
- Releases: 0
Topics
Metadata Files
README.md
Social Signal Processing for Android
SSJ is an extensible android framework for social signal processing in an out of lab envirnoment. It packages common signal processing tools in a flexible, mobile friendly Java library which can be easily integrated into Android Apps.
Features
- Realtime signal processing using independent components as processing steps in a pipeline
- Synchronized data streams
- Support for most standard android sensors e.g. Camera, Microphone, Acceleration, GPS
- Support for external sensors via bluetooth e.g. Microsoft Band 2, Myo, Angel Sensor, Empatica
- Advanced signal processing functionality, including machine learning approaches (Neural Networks, SVM, NaiveBayes)
- On device model training capabilities (batch and online learning)
- I/O functionality: local storage, sockets, bluetooth
- Energy efficient processing thanks to advanced sleep state management and support for discrete data propagation
- Live data visualization (using GraphView library)
- SSJ Creator: Android App for building, editing and running SSJ pipelines without writing a single line of code
Download
To use libssj in your own application, download the latest .aar file from the releases section, place it under app/libs/ and include the following line in your app's gradle file:
implementation files('libs/libssj-0.7.8.aar')
The latest version of the SSJ Creator app can be downloaded from the releases section as well. Alternatively, an older version is available in the Google Play Store.
Documentation
- White-paper: frontiersin.org
- Api (Javadoc): http://hcmlab.github.io/ssj/api
- Example pipeline: Github wiki
About
The Social Signal Processing for Java/Android (SSJ) framework is being developed at the Lab for Human Centered Multimedia of the University of Augsburg. The authors of the framework are: Ionut Damian, Michael Dietz, Frank Gaibler, Daniel Langerenken, Simon Flutura, Vitalijs Krumins, Antonio Grieco.
SSJ has been inspired by the SSI (http://openssi.net) framework. SSJ is not a one-to-one port of SSI to Java, it is an approximation. Nevertheless, it borrows a lot of programming patterns from SSI and preserves the same vision for signal processing which makes SSI great. It than packages everything in a flexible, mobile friendly Java library which can be easily integrated into Android Apps.
If you use SSJ for a research project, please reference the following papers:
- Ionut Damian, Michael Dietz, Elisabeth Andr, The SSJ Framework: Augmenting Social Interactions Using Mobile Signal Processing and Live Feedback, Frontiers in ICT, 2018
paper | BibTex - Ionut Damian, Michael Dietz, Frank Gaibler, Elisabeth Andr, Social Signal Processing for Dummies, In Proceedings of International Conference on Multimodal Interaction (ICMI), ACM, 2016
paper | BibTex | dl.acm.org
License
This library is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 3 of the License, or any later version.
This library is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.
You should have received a copy of the GNU General Public License along with this library; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA
Owner
- Name: Human Centered Artifical Intelligence
- Login: hcmlab
- Kind: organization
- Location: Augsburg, Germany
- Website: www.hcai.eu
- Repositories: 29
- Profile: https://github.com/hcmlab
Human Centered Artifical Intelligence Lab of the Augsburg University
GitHub Events
Total
Last Year
Issues and Pull Requests
Last synced: over 2 years ago
All Time
- Total issues: 5
- Total pull requests: 36
- Average time to close issues: about 1 month
- Average time to close pull requests: about 16 hours
- Total issue authors: 5
- Total pull request authors: 3
- Average comments per issue: 1.0
- Average comments per pull request: 0.03
- Merged pull requests: 33
- Bot issues: 0
- Bot pull requests: 0
Past Year
- Issues: 1
- Pull requests: 0
- Average time to close issues: 4 days
- Average time to close pull requests: N/A
- Issue authors: 1
- Pull request authors: 0
- Average comments per issue: 2.0
- Average comments per pull request: 0
- Merged pull requests: 0
- Bot issues: 0
- Bot pull requests: 0
Top Authors
Issue Authors
- HelenParr (1)
- ionut-damian (1)
- nahap (1)
- anharismail (1)
- ashleykolodziej (1)
Pull Request Authors
- vchernobyl (22)
- toni1991 (12)
- ionut-damian (2)
Top Labels
Issue Labels
Pull Request Labels
Packages
- Total packages: 1
- Total downloads: unknown
- Total dependent packages: 0
- Total dependent repositories: 0
- Total versions: 14
repo1.maven.org: com.github.hcmlab:libssj
Social Signal Processing for Android
- Homepage: https://github.com/hcmlab/ssj
- Documentation: https://appdoc.app/artifact/com.github.hcmlab/libssj/
- License: GNU GENERAL PUBLIC LICENSE, Version 3
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Latest release: 0.7.6
published about 6 years ago
Rankings
Dependencies
- androidx.appcompat:appcompat 1.0.2 implementation
- io.reactivex.rxjava3:rxandroid 3.0.0 api
- io.reactivex.rxjava3:rxjava 3.0.0 api
- org.tensorflow:tensorflow-lite 2.3.0 api
- org.tensorflow:tensorflow-lite-gpu 2.3.0 api
- androidx.appcompat:appcompat 1.0.2 implementation
- androidx.core:core-ktx 1.6.0 implementation
- androidx.multidex:multidex 2.0.1 implementation
- org.jetbrains.kotlin:kotlin-stdlib-jdk7 $kotlin_version implementation