Semantic and depth learning for autonomous forest mapping (2023)
Source: Proceedings. Conference titles: Latin American Robotics Symposium - LARS. Unidade: ICMC
Subjects: APRENDIZADO COMPUTACIONAL, VISÃO COMPUTACIONAL, ROBÓTICA, FLORESTAS
ABNT
NARDARI, Guilherme Vicentim e ROMERO, Roseli Aparecida Francelin. Semantic and depth learning for autonomous forest mapping. 2023, Anais.. Piscataway: IEEE, 2023. Disponível em: https://doi.org/10.1109/LARS/SBR/WRE59448.2023.10332962. Acesso em: 07 set. 2024.APA
Nardari, G. V., & Romero, R. A. F. (2023). Semantic and depth learning for autonomous forest mapping. In Proceedings. Piscataway: IEEE. doi:10.1109/LARS/SBR/WRE59448.2023.10332962NLM
Nardari GV, Romero RAF. Semantic and depth learning for autonomous forest mapping [Internet]. Proceedings. 2023 ;[citado 2024 set. 07 ] Available from: https://doi.org/10.1109/LARS/SBR/WRE59448.2023.10332962Vancouver
Nardari GV, Romero RAF. Semantic and depth learning for autonomous forest mapping [Internet]. Proceedings. 2023 ;[citado 2024 set. 07 ] Available from: https://doi.org/10.1109/LARS/SBR/WRE59448.2023.10332962