Zobrazeno 1 - 5
of 5
pro vyhledávání: '"Toluwanimi Akinyemi"'
Autor:
Wenjing Du, Guanlin Yi, Olatunji Mumini Omisore, Wenke Duan, Xingyu Chen, Toluwanimi Akinyemi, Jiang Liu, Boon‐Giin Lee, Lei Wang
Publikováno v:
Advanced Intelligent Systems, Vol 6, Iss 4, Pp n/a-n/a (2024)
Existing surgical guidewire endpoint localization methods in X‐ray images face challenges owing to their small size, simple appearance, nonrigid nature of objects, low signal‐to‐noise ratio of X‐ray images, and imbalance between the number of
Externí odkaz:
https://doaj.org/article/ae9a95e80d4c4384ac1099360e3e5133
Autor:
Wenke Duan, Toluwanimi Akinyemi, Wenjing Du, Jun Ma, Xingyu Chen, Fuhao Wang, Olatunji Omisore, Jingjing Luo, Hongbo Wang, Lei Wang
Publikováno v:
Micromachines, Vol 14, Iss 1, p 197 (2023)
Prior methods of patient care have changed in recent years due to the availability of minimally invasive surgical platforms for endovascular interventions. These platforms have demonstrated the ability to improve patients’ vascular intervention out
Externí odkaz:
https://doaj.org/article/a8357f2cc47348acb7da1734effa8efe
Publikováno v:
Micromachines, Vol 11, Iss 11, p 1021 (2020)
Research and industrial studies have indicated that small size, low cost, high precision, and ease of integration are vital features that characterize microelectromechanical systems (MEMS) inertial sensors for mass production and diverse applications
Externí odkaz:
https://doaj.org/article/39ec61fc47404d22ad4e62dcd9f2fb58
Autor:
Zhengrong Lai, Yifa Li, Weimin Wang, Wenke Duan, Wenjing Du, Olatunji Mumini Omisore, Toluwanimi Akinyemi
Publikováno v:
2021 6th International Conference on Robotics and Automation Engineering (ICRAE).
Lack of learning-based methods for characterizing the multimodal data generated during cyborg catheterization hinders the drive towards autonomous robotic control. Also, multiplexing salient features from multiple data-sources can enhance effective a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3dcfc39e7336e43c95671e0f862405e4
https://doi.org/10.36227/techrxiv.16908403.v1
https://doi.org/10.36227/techrxiv.16908403.v1