Zobrazeno 1 - 10
of 23
pro vyhledávání: '"Ba-Viet Ngo"'
Publikováno v:
AgriEngineering, Vol 4, Iss 4, Pp 871-887 (2022)
Tomato leaves can have different diseases which can affect harvest performance. Therefore, accurate classification for the early detection of disease for treatment is very important. This article proposes one classification model, in which 16,010 tom
Externí odkaz:
https://doaj.org/article/a4666f6a115146a3aa3c8bcd08d145e0
Publikováno v:
Applied Computer Science, Vol 18, Iss 3, Pp 19-30 (2022)
The determination of the R peak position in the ECG signal helps physicians not only to know the heart rate per minute, but also to monitor the patient’s health related to heart disease. This paper proposes a system to accurately determine the R pe
Externí odkaz:
https://doaj.org/article/5f33670d1f0447cea2458e4181e913ca
Publikováno v:
Micromachines, Vol 14, Iss 7, p 1411 (2023)
Soft sensors are attracting much attention from researchers worldwide due to their versatility in practical projects. There are already many applications of soft sensors in aspects of life, consisting of human-robot interfaces, flexible electronics,
Externí odkaz:
https://doaj.org/article/825b8997877245dcaea37613b0c44339
Autor:
Ba-Viet Ngo, Thanh-Hai Nguyen
Publikováno v:
Applied Sciences, Vol 12, Iss 17, p 8880 (2022)
A semi-automatic wheelchair allows disabled people to possibly control in an indoor environment with obstacles and targets. The paper proposes an EEG-based control system for the wheelchair based on a grid map designed to allow disabled people to rea
Externí odkaz:
https://doaj.org/article/afbe361a5f0a4d9a8990e51a4a2bc1bc
Autor:
Ba-Viet Ngo, Thanh-Hai Nguyen
Self-mobility electric wheelchairs are very useful for people with disabilities, so they can move without help in indoor environments. To create one selfmobility electric wheelchair, modern methods for control such as computer vision and machine lear
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5e4d0f60620375bc3e6037407eedcab0
https://zenodo.org/record/8128776
https://zenodo.org/record/8128776
Publikováno v:
AgriEngineering; Volume 4; Issue 4; Pages: 871-887
Tomato leaves can have different diseases which can affect harvest performance. Therefore, accurate classification for the early detection of disease for treatment is very important. This article proposes one classification model, in which 16,010 tom
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a86c2f7222496b0c97a76f8750936d34
Publikováno v:
2022 6th International Conference on Green Technology and Sustainable Development (GTSD).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9e8dc5dd9fcef2a71845df204cc6d9fb
https://doi.org/10.1109/gtsd54989.2022.9989206
https://doi.org/10.1109/gtsd54989.2022.9989206
Autor:
Dang-Khoa Tran, Thanh-Hai Nguyen, Ba-Viet Ngo, Minh-Ly Lai, Thi-My-Kieu Ong, Thi-Minh Vu, Van-Minh Nguyen
Publikováno v:
2022 6th International Conference on Green Technology and Sustainable Development (GTSD).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e4f9d48bd3e3e0a4e48f6283e9e31c68
https://doi.org/10.1109/gtsd54989.2022.9989065
https://doi.org/10.1109/gtsd54989.2022.9989065
Publikováno v:
European Journal of Engineering and Technology Research. 6:130-138
This paper aims to reconstruct 3D map based on environmental 3D cloud information of landmarks. A Modified Iterative Closest Point (MICP) algorithm is proposed to apply for merging point clouds through a transformation matrix with values updated usin
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::409ba3c16bf6bb0cda9c19882ac2a7a0
https://doi.org/10.24018/ejeng.2021.6.3.2421
https://doi.org/10.24018/ejeng.2021.6.3.2421
Publikováno v:
2021 15th International Conference on Advanced Computing and Applications (ACOMP).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ee46b933c81298b8070c56c81c48b934
https://doi.org/10.1109/acomp53746.2021.00031
https://doi.org/10.1109/acomp53746.2021.00031