Machine Learning Based Techniques for Path Prediction

Abstract

Path prediction aims at producing safer systems by allowing them to anticipate the outcomes of road scenes situations. Lately, machine learning methods have been used extensively for that purpose. Neural networks in particular with architectures such as RNN, LSTM, CNN, and self-attention. They offer the best results with the commonly used metrics. However, these evaluation criteria do not guarantee safety and can be criticized. More requirements should be met than the minimization of a few metrics.

Date
Oct 22, 2019
Location
Berlin, Germany
Jean Mercat
Jean Mercat
Research Scientist in ML

My research interests include Scientific Computing, Robotics, and Neural Networks.

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