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...

Full description

Saved in:

Bibliographic Details
Published in:	Discover Artificial Intelligence Vol. 5; no. 1; pp. 68 - 15
Main Authors:	Zhang, Hui, Shen, Dawang
Format:	Journal Article
Language:	English
Published:	Cham Springer International Publishing 01.12.2025 Springer Nature B.V Springer
Subjects:	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
Online Access:	Get full text
Tags:	Add Tag No Tags, Be the first to tag this record!

Be the first to leave a comment!