Zobrazeno 1 - 10
of 253
pro vyhledávání: '"Kin Choong Yow"'
Autor:
Soheil Vosta, Kin-Choong Yow
Publikováno v:
IEEE Access, Vol 12, Pp 2198-2209 (2024)
Violent behaviour is always an important issue that threatens any society. Therefore, many organizations have used surveillance cameras to monitor such events to preserve public safety and mitigate potential harm. It is difficult for human operators
Externí odkaz:
https://doaj.org/article/1d698ab2cfc144479dcd7920df87390b
Autor:
Stefano Frizzo Stefenon, Gurmail Singh, Bruno José Souza, Roberto Zanetti Freire, Kin‐Choong Yow
Publikováno v:
IET Generation, Transmission & Distribution, Vol 17, Iss 15, Pp 3501-3511 (2023)
Abstract To ensure the electrical power supply, inspections are frequently performed in the power grid. Nowadays, several inspections are conducted considering the use of aerial images since the grids might be in places that are difficult to access.
Externí odkaz:
https://doaj.org/article/67b16cfcd56f4fdfa666a2a4d2a1774c
Publikováno v:
IEEE Access, Vol 11, Pp 142146-142161 (2023)
Deep learning has been widely used in computer vision applications and it has been shown to achieve state-of-the-art results in many applications including self-driving cars. Despite the great progress, less attention has been paid to the safety-leve
Externí odkaz:
https://doaj.org/article/0ae933d1a70a46e3bb1b415f811631e8
Publikováno v:
IEEE Access, Vol 11, Pp 137352-137365 (2023)
The high number of hospitalization cases of COVID-19 made public health providers overloaded. Forecasting the number of hospitalized patients related to COVID-19 can help public health providers make informed decisions for controlling the spread. In
Externí odkaz:
https://doaj.org/article/b86c11665f4645cd823d1f904053094f
Autor:
Stéfano Frizzo Stefenon, Marcelo Picolotto Corso, Ademir Nied, Fabio Luis Perez, Kin‐Choong Yow, Gabriel Villarrubia Gonzalez, Valderi Reis Quietinho Leithardt
Publikováno v:
IET Generation, Transmission & Distribution, Vol 16, Iss 6, Pp 1096-1107 (2022)
Abstract Insulators of the electrical power grid are usually installed outdoors, so they suffer from environmental stresses, such as the presence of contamination. Contamination can increase surface conductivity, which can lead to system failures, re
Externí odkaz:
https://doaj.org/article/2188b0b639794b7d91ebb5233077202a
Publikováno v:
IEEE Access, Vol 10, Pp 97780-97793 (2022)
In recent years, computer networks have become an indispensable part of our life, and these networks are vulnerable to various type of network attacks, compromising the security of our data and the freedom of our communications. In this paper, we pro
Externí odkaz:
https://doaj.org/article/195bcb3ea92b4a909d37cb7be3575d72
Publikováno v:
IEEE Access, Vol 10, Pp 81054-81070 (2022)
The smart grid connects components of power systems and communication networks in an interdependent two-way system that delivers electricity to consumers and collects data that enables it to react to usage levels and interference from threats, such a
Externí odkaz:
https://doaj.org/article/7ee4b7fa941642778ed39310f2677ab2
Autor:
Gurmail Singh, Kin-Choong Yow
Publikováno v:
IEEE Access, Vol 9, Pp 85198-85208 (2021)
Timely and accurate detection of an epidemic/pandemic is always desired to prevent its spread. For the detection of any disease, there can be more than one approach including deep learning models. However, transparency/interpretability of the reasoni
Externí odkaz:
https://doaj.org/article/3dd4c9f2039745d3a334d3538e170d41
Autor:
Gurmail Singh, Kin-Choong Yow
Publikováno v:
IEEE Access, Vol 9, Pp 41482-41493 (2021)
Interpretation of the reasoning process of a prediction made by a deep learning model is always desired. However, when it comes to the predictions of a deep learning model that directly impacts on the lives of people then the interpretation becomes a
Externí odkaz:
https://doaj.org/article/19e24268aa344adab2f3bb7d08038117
Publikováno v:
IEEE Access, Vol 7, Pp 165103-165121 (2019)
In this paper, we propose an efficient online multi-object tracking method based on the Gaussian mixture probability hypothesis density (GMPHD) filter and occlusion group management scheme where a hierarchical data association is utilized for the GMP
Externí odkaz:
https://doaj.org/article/996004ec567b4991993c58e2e09cc00e