A particle filtering (PF) is a sequential Bayesian filtering method suitable for non-linear non-
Gaussian systems, which is widely used to estimate the states of parameters of interest that …

Particle filtering (PF) is a sequential Monte Carlo method that draws sample (particle) values
of state variables of interest to approximate the posterior probability distribution function …

Cow tail detection and tracking in videos provide valuable information for individual
identification, calving process, behavior analysis, and body condition monitoring. Although …

Biogeography-based optimization (BBO) has gained significant popularity as a population-
based metaheuristic optimization algorithm. However, the existing variants of BBO …

The process of direct metal deposition for cladding has become extremely popular. Online
condition monitoring of the process is necessary to obtain a desired clad geometry. The …

Moving object tracking is one of the applied fields in artificial intelligence and robotic. The
main objective of object tracking is to detect and locate targets in video frames of real …

To provide effective resolutions for complex real-life problems and other optimization
problems, abundant, various procedures have been presented in the last few decades. This …

Particle filter (PF) is introduced to tackle the limitations of the Kalman filter which adopts
Gaussian in the state and noise of the system. PFs have the problem of sample …

With the distended utilization of reconnaissance mission cameras. A library is proffered
during this paper that is employed to try to image preparing victimization programming …

The new research trend is to achieve improved elucidation efficiency in the area of global
optimization for various functional and real‐life applications. Various nature inspired …