Difference between revisions of "Software"
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Here we enumerate different software packages developed by our group: | Here we enumerate different software packages developed by our group: | ||
| − | ==PeTra (People | + | ==PeTra (People Tracker)== |
PeTra is a tool which allows detecting and tracking people. The system is based on a CNN that uses an occupancy map constructed from the readings of a LIDAR sensor. | PeTra is a tool which allows detecting and tracking people. The system is based on a CNN that uses an occupancy map constructed from the readings of a LIDAR sensor. | ||
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https://github.com/PierreExeter/jaco-gym | https://github.com/PierreExeter/jaco-gym | ||
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| + | == DOROTHEA (DOcker-based fRamework fOr gaTHering nEtflow trAffic) == | ||
| + | |||
| + | DOROTHEA is a Docker-based solution to build packet flow datasets. It uses a NetFlow sensor which collects the streams of packets that pass through a network interface. The tool simulates a complex and realistic computer network. It is easily configurable and scalable, for instance it is possible to set the number of computers that generate network traffic. A threshold can be set to define the number of packets used to create flows, thus emulating the real functionality of routers. | ||
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| + | More information at https://seguridad.unileon.es/index.php/DOROTHEA | ||
| + | |||
| + | == MoEv (Model Evaluator) == | ||
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| + | MoEv is a general-purpose tool that allows for building classification models from labeled datasets. Besides, MoEv allows for performing data cleaning and pre-processing operations. It has been successfully used in different research areas such us jamming attacks detection on real-time location systems, academic success prediction at educational institutions, or network attacks detection. | ||
| + | |||
| + | More information at https://seguridad.unileon.es/index.php/MoEv | ||
Revision as of 09:59, 5 November 2020
Here we enumerate different software packages developed by our group:
Contents
PeTra (People Tracker)
PeTra is a tool which allows detecting and tracking people. The system is based on a CNN that uses an occupancy map constructed from the readings of a LIDAR sensor.
Dataset: https://www.frontiersin.org/articles/10.3389/fnbot.2017.00072/full PeTra: https://www.frontiersin.org/articles/10.3389/fnbot.2018.00085/full https://www.mdpi.com/2218-6581/8/3/75
https://github.com/ClaudiaAlvarezAparicio/petra
BRITTANY (Biometric RecognITion Through gAit aNalYsis)
Brittany is a tool which allows a Biometric recognition through gait analysis by using LIDAR sensors. The system is based on a classification neural network which allow identify 5 diferent users of the system or intruders in it.
https://github.com/ClaudiaAlvarezAparicio/brittany
SUFFER (SimUlation Framework for Education in Robotics)
Robot as a Service (RaaS) platform for simulating robots.
More information in Innovacionfrentealvirus
Jaco gym (Reinforcement Learning for Manipulators)
Pierre has been using Gazebo for trainning
https://github.com/PierreExeter/jaco-gym
DOROTHEA (DOcker-based fRamework fOr gaTHering nEtflow trAffic)
DOROTHEA is a Docker-based solution to build packet flow datasets. It uses a NetFlow sensor which collects the streams of packets that pass through a network interface. The tool simulates a complex and realistic computer network. It is easily configurable and scalable, for instance it is possible to set the number of computers that generate network traffic. A threshold can be set to define the number of packets used to create flows, thus emulating the real functionality of routers.
More information at https://seguridad.unileon.es/index.php/DOROTHEA
MoEv (Model Evaluator)
MoEv is a general-purpose tool that allows for building classification models from labeled datasets. Besides, MoEv allows for performing data cleaning and pre-processing operations. It has been successfully used in different research areas such us jamming attacks detection on real-time location systems, academic success prediction at educational institutions, or network attacks detection.
More information at https://seguridad.unileon.es/index.php/MoEv
