Search Results for author: Jinn-Liang Liu

Found 4 papers, 0 papers with code

End-to-End Deep Learning of Lane Detection and Path Prediction for Real-Time Autonomous Driving

no code implementations9 Feb 2021 Der-Hau Lee, Jinn-Liang Liu

Inspired by the UNet architecture of semantic image segmentation, we propose a lightweight UNet using depthwise separable convolutions (DSUNet) for end-to-end learning of lane detection and path prediction (PP) in autonomous driving.

Autonomous Driving Image Segmentation +2

Differential Capacitance of Electric Double Layers: A Poisson-Bikerman Formula

no code implementations24 Dec 2020 Ren-Chuen Chen, Chin-Lung Li, Jen-Hao Chen, Bob Eisenberg, Jinn-Liang Liu

The PBik theory is a generalization of the classical Poisson-Boltzmann theory to include different steric energies of different-sized ions and water similar to different electrical energies for different-charged ions.

Soft Condensed Matter

Deep Learning and Control Algorithms of Direct Perception for Autonomous Driving

no code implementations26 Oct 2019 Der-Hau Lee, Kuan-Lin Chen, Kuan-Han Liou, Chang-Lun Liu, Jinn-Liang Liu

Based on the direct perception paradigm of autonomous driving, we investigate and modify the CNNs (convolutional neural networks) AlexNet and GoogLeNet that map an input image to few perception indicators (heading angle, distances to preceding cars, and distance to road centerline) for estimating driving affordances in highway traffic.

Autonomous Driving

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