Lmst

#LocationClassification

It's been a pleasure to present our #DeepLearning from Trajectory Data review paper at #BMDA2023

https://www.datastories.org/bmda23/BMDA23Program.html

Our review covers 8 use cases:
1. #LocationClassification
2. #ArrivalTimePrediction
3. #TrafficFlow #prediction
4. #Trajectory prediction
5. Trajectory #classification
6. Next location prediction
7. #AnomalyDetection
8. #SyntheticDataGeneration

The price for most surprising approach 🏆 goes to natural language #NLP #Transfomers for #Traffic volume prediction

Screenshot of the intro slide of my talk titled:

Deep Learning From Trajectory Data - A Review of Deep Neural Networks and the Trajectory Data Representations to Train Them

presented at the Big Mobility Data Analytics (BMDA) workshop at EDBT/ICDT Conference
on 2023-03-28

authored by
Anita Graser, Anahid Jalali, Jasmin Lampert, Axel Weißenfeld and Krzysztof Janowicz

This work is mainly funded by the EU’s Horizon Europe research and innovation program under Grant No. 101070279 MobiSpaces and No. 101021797 STARLIGHT.

Slide on the traffic volume prediction use case, highlighting a paper using NLP Transformers

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