SLOAM: semantic lidar odometry and mapping for forest inventory (2020)
Source: IEEE Robotics and Automation Letters. Unidade: ICMC
Subjects: VISÃO COMPUTACIONAL, REALIDADE VIRTUAL, ROBÓTICA, APRENDIZADO COMPUTACIONAL, AGRICULTURA DE PRECISÃO
ABNT
CHEN, Steven W et al. SLOAM: semantic lidar odometry and mapping for forest inventory. IEEE Robotics and Automation Letters, v. 5, n. 2, p. 612-619, 2020Tradução . . Disponível em: https://doi.org/10.1109/LRA.2019.2963823. Acesso em: 18 nov. 2024.APA
Chen, S. W., Nardari, G. V., Lee, E. S., Qu, C., Liu, X., Romero, R. A. F., & Kumar, V. (2020). SLOAM: semantic lidar odometry and mapping for forest inventory. IEEE Robotics and Automation Letters, 5( 2), 612-619. doi:10.1109/LRA.2019.2963823NLM
Chen SW, Nardari GV, Lee ES, Qu C, Liu X, Romero RAF, Kumar V. SLOAM: semantic lidar odometry and mapping for forest inventory [Internet]. IEEE Robotics and Automation Letters. 2020 ; 5( 2): 612-619.[citado 2024 nov. 18 ] Available from: https://doi.org/10.1109/LRA.2019.2963823Vancouver
Chen SW, Nardari GV, Lee ES, Qu C, Liu X, Romero RAF, Kumar V. SLOAM: semantic lidar odometry and mapping for forest inventory [Internet]. IEEE Robotics and Automation Letters. 2020 ; 5( 2): 612-619.[citado 2024 nov. 18 ] Available from: https://doi.org/10.1109/LRA.2019.2963823