Zobrazeno 1 - 5
of 5
pro vyhledávání: '"Siqiu Guo"'
Autor:
Siqiu Guo
Publikováno v:
Light: Science & Applications, Vol 12, Iss 1, Pp 1-10 (2023)
Editorial Nanophotonics has emerged as a cutting-edge interdisciplinary research field today. Its primary objective is to leverage the interaction between light and matter at the wavelength and sub-wavelength scales, with the purpose of designing and
Externí odkaz:
https://doaj.org/article/4323cf48871d48efbb06147e415f47b8
Autor:
Siqiu Guo
Publikováno v:
Light: Science & Applications, Vol 12, Iss 1, Pp 1-8 (2023)
Editorial My first encounter with Prof. Fan Wang left a profound impression on me. I felt that he was exactly the gentle and courteous scholar depicted in books, well-read in poetry and literature, and exceptionally talented. Through my interactions
Externí odkaz:
https://doaj.org/article/a14a4d3adf9c43f1be4b628447ed92ec
Autor:
Siqiu Guo
Publikováno v:
Light: Science & Applications, Vol 11, Iss 1, Pp 1-5 (2022)
Editorial Integrated photonics means integrating multiple photonic functions on a single Photonic Integrated Chip (PIC). Empowered by various nanofabrication techniques on diverse innovative material platforms, remarkable advances have been made in i
Externí odkaz:
https://doaj.org/article/739111a90fbd4c7496d162c490b4d723
Color Feature-Based Object Tracking through Particle Swarm Optimization with Improved Inertia Weight
Publikováno v:
Sensors, Vol 18, Iss 4, p 1292 (2018)
This paper presents a particle swarm tracking algorithm with improved inertia weight based on color features. The weighted color histogram is used as the target feature to reduce the contribution of target edge pixels in the target feature, which mak
Externí odkaz:
https://doaj.org/article/19cf1a4163cb4e77914843619ebbda0b
Color Feature-Based Object Tracking through Particle Swarm Optimization with Improved Inertia Weight
Publikováno v:
Sensors, Vol 18, Iss 4, p 1292 (2018)
Sensors; Volume 18; Issue 4; Pages: 1292
Sensors (Basel, Switzerland)
Sensors; Volume 18; Issue 4; Pages: 1292
Sensors (Basel, Switzerland)
This paper presents a particle swarm tracking algorithm with improved inertia weight based on color features. The weighted color histogram is used as the target feature to reduce the contribution of target edge pixels in the target feature, which mak
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::771ea4085fc4aac9875886a32e4a772d
https://doi.org/10.3390/s18041292
https://doi.org/10.3390/s18041292