ETLi: Efficiently annotated traffic LiDAR dataset using incremental and suggestive annotation

ETLi: Efficiently annotated traffic LiDAR dataset using incremental and suggestive annotation

Autonomous driving requires a computerized perception of the environment for safety and machine‐learning evaluation. Recognizing semantic information is difficult, as the objective is to instantly recognize and distinguish items in the environment. Training a model with real‐time semantic capability...

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Bibliographic Details
Main Authors: Jungyu Kang, Seung‐Jun Han, Nahyeon Kim, Kyoung‐Wook Min
Format: Article
Language:English
Published: Electronics and Telecommunications Research Institute (ETRI) 2021-09-01
Series:ETRI Journal
Subjects:
autonomous driving
deep‐learning dataset
light detection and ranging
semantic segmentation
semantic simultaneous localization and mapping
Online Access:https://doi.org/10.4218/etrij.2021-0055

Internet

https://doi.org/10.4218/etrij.2021-0055

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