Apr 11, 2019 · We combine a novel approach to automatic training data creation, making use of stereoscopic visual odometry, with a state-of-the-art CNN ...
In this work we propose a new approach to this problem, whereby instead of learning to predict immediate driver control inputs, we train a deep convolutional.
This work proposes a new approach to automatic training data creation, making use of stereoscopic visual odometry, with a state-of-the-art CNN architecture ...
We combine a novel approach to automatic training data creation, making use of stereoscopic visual odometry, with a state-of-the-art CNN architecture to map a ...
We combine a novel approach to automatic training data creation, making use of stereoscopic visual odometry, with a state-of-the-art CNN architecture to map a ...
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Posted: Aug 26, 2021
Posted: Aug 26, 2021
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Feb 9, 2021 · These results show that DSUNet is efficient and effective for lane detection and path prediction in autonomous driving. Comments: 6 pages, 4 ...
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Abstract—We present an end-to-end imitation learning sys- tem for agile, off-road autonomous driving using only low-cost on-board sensors.
Apr 22, 2022 · DSUNet-PP outperforms a modified UNet in lateral error, which is tested in a real car on real road. These results show that DSUNet is efficient ...
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