Automated Organization ProfileDepartment of Artificial Intelligence of Lviv National University "Lviv Polytechnic"
Department of Artificial Intelligence of Lviv National University "Lviv Polytechnic"
Current S-Index
Sum of Dataset Indices for all datasets
Average Dataset Index per Dataset
Average Dataset Index per dataset
Total Datasets
Total datasets in this organization
Average FAIR Score
Average FAIR Score per dataset
Total Citations
Total citations to the organization's datasets
Total Mentions
Total mentions of the organization's datasets
S-Index Interpretation
The S-Index (Sharing Index) is a comprehensive metric that represents the cumulative impact of all your datasets. It is calculated as the sum of Dataset Index scores across all your claimed datasets.
What it means:
- A higher S-index indicates greater overall impact of your datasets relative to typical datasets in their fields of research
- The S-Index grows as you add more datasets or as existing datasets gain more citations and mentions
- It provides a single number to track your research data impact over time
Current S-Index: 3.1 (sum of 2 datasets Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
This dataset contains flight data collected from simulations of an autonomous quadrotor UAV using the AirSim simulation platform.The dataset was specifically designed for the comparative evaluation of two reinforcement learning algorithms: Asynchronous Advantage Actor-Critic (A3C) and Deep Deterministic Policy Gradient (DDPG). The data enables the reproduction of key performance metrics, such as trajectory tracking accuracy (RMSE), control stability (CSI), energy consumption, and response time.
Authors
- Petrenko, Dmytro
This dataset contains flight data collected from simulations of an autonomous quadrotor UAV using the AirSim simulation platform.The dataset was specifically designed for the comparative evaluation of two reinforcement learning algorithms: Asynchronous Advantage Actor-Critic (A3C) and Deep Deterministic Policy Gradient (DDPG). The data enables the reproduction of key performance metrics, such as trajectory tracking accuracy (RMSE), control stability (CSI), energy consumption, and response time.
Authors
- Petrenko, Dmytro