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Pedestrian Trajectory Prediction for Real-Time Autonomous Systems via Context-Augmented Transformer Networks
Forecasting the trajectory of pedestrians in shared urban traffic environments from non-invasive sensor modalities is still considered one of the challenging problems facing the development of autonomous vehicles (AVs). In the literature, this problem is often tackled using recurrent neural networks...
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
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MDPI
2022
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| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9572723/ https://www.ncbi.nlm.nih.gov/pubmed/36236592 http://dx.doi.org/10.3390/s22197495 |