Optimization of particle filter tracking algorithm based on weakly supervised attribute learning

This study proposes an optimization method for particle filter tracking algorithm to solve the issues of low recognition efficiency and poor tracking accuracy faced by existing target tracking algorithms in complex environments. This method combines weakly supervised learning with energy function op...

Celý popis

Uloženo v:

Podrobná bibliografie
Vydáno v:	Discover Artificial Intelligence Ročník 5; číslo 1; s. 68 - 15
Hlavní autoři:	Zhang, Hui, Shen, Dawang
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Cham Springer International Publishing 01.12.2025 Springer Nature B.V Springer
Témata:	Accuracy Algorithms Artificial Intelligence Classification Computer Science Computer vision Efficiency Engineering Lighting Methods Object detection Optimization Particle filtering algorithm Support vector machines Target tracking Tracking accuracy Weakly supervised attribute learning Tracking accuracy Target tracking Weakly supervised attribute learning Particle filtering algorithm Object detection
ISSN:	2731-0809, 2731-0809
On-line přístup:	Získat plný text
Tagy:	Přidat tag Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!

Buďte první, kdo okomentuje tento záznam!