Dec 15, 2023 · The proposed system outperforms all existing networks on Indian roads with an accuracy of 75.28% in obstacle detection and 91.36% in lane ...
Dec 15, 2023 · The proposed LaneScanNET uses a parallel pipeline with an Obstacle Detection Network (ODN) and a Lane Detection Network (LDN) to simultaneously ...
LaneScanNET proposes a novel deep-learning network for obstacle-lane detection in autonomous driving, outperforming existing models with 91.36% accuracy in lane ...
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LaneScanNET: A deep-learning approach for simultaneous detection of obstacle-lane states for autonomous driving systems.
Jul 8, 2023 · LaneScanNET: A deep-learning approach for simultaneous detection of obstacle-lane states for autonomous driving systems · Expert Systems with ...
(2017) [25]. The proposed approach supports driver assistance systems that detect objects around the vehicle, thereby using efficient feature extraction and ...
Jul 18, 2023 · I am delighted to share the fantastic news that our research paper, titled "LaneScanNET: A deep-learning approach for simultaneous detection ...
Apr 3, 2024 · LaneScanNET: A deep-learning approach for simultaneous detection of obstacle-lane states for autonomous driving systems. Expert Systems with ...
LaneScanNET: A deep-learning approach for simultaneous detection of obstacle-lane states for autonomous driving systems. PS Perumal, Y Wang, M Sujasree, S ...
Jan 10, 2024 · p>Autonomous vehicles have been a recent trend and active research area from the onset of machine learning and deep learning algorithms.
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