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Found 5 papers, 3 papers with code
Heterogeneous Graph-based Trajectory Prediction using Local Map Context and Social Interactions
Precisely predicting the future trajectories of surrounding traffic participants is a crucial but challenging problem in autonomous driving, due to complex interactions between traffic agents, map context and traffic rules.
XTSC-Bench: Quantitative Benchmarking for Explainers on Time Series Classification
Despite the growing body of work on explainable machine learning in time series classification (TSC), it remains unclear how to evaluate different explainability methods.
Literature Review: Computer Vision Applications in Transportation Logistics and Warehousing
Computer vision applications in transportation logistics and warehousing have a huge potential for process automation.
TSInterpret: A unified framework for time series interpretability
With the increasing application of deep learning algorithms to time series classification, especially in high-stake scenarios, the relevance of interpreting those algorithms becomes key.
Knowledge Fusion via Embeddings from Text, Knowledge Graphs, and Images
We present a baseline approach for cross-modal knowledge fusion.
