Zobrazeno 1 - 4
of 4
pro vyhledávání: '"Jordan LeNoach"'
Publikováno v:
2021 IEEE 24th International Conference on Information Fusion (FUSION).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::85c80a49a8b3dc77c8056811af5d4c20
https://doi.org/10.23919/fusion49465.2021.9627041
https://doi.org/10.23919/fusion49465.2021.9627041
Publikováno v:
2021 IEEE Aerospace Conference (50100).
This paper introduces a multiple-model Ornstein-Uhlenbeck (MM-OU) formulation of target motion uncertainty. This model exploits a weighted set of learned motion trajectories for targets. Each realization of target motion is governed by one trajectory
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6b8dc8bb85836e33a476c7f8719e4cec
https://doi.org/10.1109/aero50100.2021.9438389
https://doi.org/10.1109/aero50100.2021.9438389
Publikováno v:
FUSION
Multi-sensor multi-target tracking requires the solution to a challenging data association problem. The problem simplifies when a portion of the target state vector and the corresponding sensor data satisfy a particular Markovian assumption. This lea
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7ff10f3c17ca871ed8a87168019fe2c9
https://doi.org/10.23919/fusion45008.2020.9190256
https://doi.org/10.23919/fusion45008.2020.9190256
Publikováno v:
Scopus-Elsevier
Europe PubMed Central
Europe PubMed Central
Purpose: To establish an inverse planning framework with adjustable voxel penalty for more conformal IMRT dose distribution as well as improved interactive controllability over the regional dose distribution of the resultant plan. Materials and Metho
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0f18eb87e843fd35de829496305a13b9
http://www.scopus.com/inward/record.url?eid=2-s2.0-78650357769&partnerID=MN8TOARS
http://www.scopus.com/inward/record.url?eid=2-s2.0-78650357769&partnerID=MN8TOARS
