Self-localisation in indoor environments combining learning and evolution with wireless networks (2014)
- Authors:
- USP affiliated authors: OSÓRIO, FERNANDO SANTOS - ICMC ; UEYAMA, JO - ICMC ; WOLF, DENIS FERNANDO - ICMC
- Unidade: ICMC
- Subjects: SISTEMAS DE INFORMAÇÃO; ENGENHARIA DE SOFTWARE; SISTEMAS DISTRIBUÍDOS; PROGRAMAÇÃO CONCORRENTE
- Language: Inglês
- Imprenta:
- ISBN: 9781450316569
- Source:
- Título: Proceedings
- Conference titles: Symposium on Applied Computing - SAC
-
ABNT
PESSIN, Gustavo et al. Self-localisation in indoor environments combining learning and evolution with wireless networks. 2014, Anais.. New York: ACM, 2014. . Acesso em: 28 dez. 2025. -
APA
Pessin, G., Osório, F. S., Ueyama, J., Wolf, D. F., Moioli, R. C., & Vargas, P. A. (2014). Self-localisation in indoor environments combining learning and evolution with wireless networks. In Proceedings. New York: ACM. -
NLM
Pessin G, Osório FS, Ueyama J, Wolf DF, Moioli RC, Vargas PA. Self-localisation in indoor environments combining learning and evolution with wireless networks. Proceedings. 2014 ;[citado 2025 dez. 28 ] -
Vancouver
Pessin G, Osório FS, Ueyama J, Wolf DF, Moioli RC, Vargas PA. Self-localisation in indoor environments combining learning and evolution with wireless networks. Proceedings. 2014 ;[citado 2025 dez. 28 ] - Evolving an indoor robotic localization system based on wireless networks
- Investigation on the evolution of an indoor robotic localization system based on wireless networks
- Evolução de redes neurais para localização de robôs móveis usando redes sem fio
- Swarm intelligence and the quest to solve a garbage and recycling collection problem
- Mobile robot indoor localization using artificial neural networks and wireless networks
- Evaluating the impact of the number of access points in mobile robots localization using artificial neural networks
- Uncovering new neural network topologies in real world robot applications
- Artificial neural nets object recognition for 3D point clouds
- CaRINA dataset: an emerging-country urban scenario benchmark for road detection systems
- Vision-based autonomous navigation using neural networks and templates in urban environments
How to cite
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
