AI/ML Challenge Finale: Multi Modal V2V Beam Prediction, Depth Map Estimation in 6G, and 3D Location Estimation
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The ITU AI/ML in 5G Challenge in 2023 (Fourth edition) offers a platform for collaboratively addressing the problems in applying AI/ML in communication networks including 5G & 6G. The Challenge connects participants (students and professionals) from more than 100 countries, with industry and academia solving real-world problems using AI/ML in communication networks. The challenge is offering 12 problem statement in 2023. Some of these problem statements includes;
- Multi Modal V2V Beam Prediction
- Depth Map Estimation in 6G mmWave systems
- 3D Location Estimation Using RSSI of Wireless LAN
The Multi Modal V2V Beam Prediction challenge revolves around crafting machine learning-based solutions that harness the power of a multi-modal sensing dataset, combining visual and positional data modalities within a V2V scenario. The ultimate goal? Predict the future optimal mmWave beam index with precision and efficiency.
Depth Map Estimation in 6G mmWave systems Challenge aimed to develop ML solutions using communication signals to perform depth map estimation.
Whilst the 3D Location Estimation Using RSSI of Wireless LAN challenge aims to develop an AI/ML-based localization algorithm that can accurately estimate the position of a receiver based on RSS information from surrounding radio transmitters including height information (enabling the estimation of the target’s 3D location).
This weinar will cover presentation from best teams of this competition and winners will be announced at the end of the session to recognize their outbstanding performance.
The winners are as follows;
Problem Statement: Multi Modal V2V Beam Prediction
- Beamwise – Winner (1st place) Prize: 500 CHF – Mattia Fabiani, Diego Silva
- Hyperion – Runner-up (2nd place) Prize: 300 CHF – Ndabuye Sengayo Gideo
Problem Statement: 3D Location Estimation Using RSSI of Wireless LAN
- Polaris – Winner (1st place) Prize: 500 CHF – Ndabuye Sengayo Gideon
Problem Statement: Depth Map Estimation in 6G mmWave systems
- HSC – Winner (1st place) Prize: 500 CHF – Jayanth S