Deep Learning for LiDAR-Based Autonomous Vehicles in Smart Cities

Ponnaganti, Vinay; Moh, Melody; Moh, Teng-Sheng

doi:10.1007/978-3-030-15145-4_65-1

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Detection and Ranging Using Deep Learning1

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2021

2022

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Cited by 6 publications

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“…In our case, deep learning is applied in object detection and pattern recognition. Similar applications of deep learning have been reported in the lidar literature using point clouds [14], for smart cities [15], and for object detection [16]. Among the deep learning algorithms, Convolutional Neural Network (CNN) is known for its extraordinary pattern recognition utility to analyze visual imagery [17].…”

Section: Detection and Ranging Using Deep Learningmentioning

confidence: 67%

Imaging lidar prototype with homography and deep learning ranging methods

Kim¹,

Chen²,

Alisafaee³

2022

J. Opt.

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We report on developing a non-scanning laser-based imaging lidar system based on a diffractive optical element with potential applications in advanced driver assistance systems, autonomous vehicles, drone navigation, and mobile devices. Our proposed lidar utilizes image processing, homography, and deep learning. Our emphasis in the design approach is on the compactness and cost of the final system for it to be deployable both as standalone and complementary to existing lidar sensors, enabling fusion sensing in the applications. This work describes the basic elements of the proposed lidar system and presents two potential ranging mechanisms, along with their experimental results demonstrating the real-time performance of our first prototype.

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