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De - Biasing 2 MIT PDF

9 Pages·2021·English
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by ['Victor Vite HM']| 2021| 9 pages| English

About De - Biasing 2 MIT

This document proposes a new method for training deep neural networks for autonomous driving using a variational autoencoder. The method allows for novelty detection by learning latent variables that characterize the training data and can identify situations with insufficient data. It also addresses training data imbalances by resampling the data distribution. The model is trained end-to-end to directly output steering commands from camera images while also learning unsupervised latent variables. This enables novelty detection to increase robustness and automated debiasing to improve training accuracy and speed. The approach was evaluated on a challenging autonomous driving dataset.

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Author:['Victor Vite HM']
Publication Year:2021
Pages:9
Language:English
Format:PDF
Price:FREE
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