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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...
Autor principal: | Saleh, Khaled |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
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 |
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