Results 31 to 40 of about 568 (133)

Extended target Poisson multi-Bernoulli mixture trackers based on sets of trajectories

2019 22th International Conference on Information Fusion (FUSION), 2019
MATLAB code is available at https://github.com/yuhsuansia/Extended-Target-PMBM-Tracker.
Yuxuan Xia, Karl Granström, Lennart Svensson, Ángel F. García-Fernández, Jason L. Williams   +4 more
openaire   +3 more sources

A high‐altitude thermal infrared method for estimating moose abundance and demography in Rocky Mountain National Park, USA

Wildlife Biology, EarlyView.
Resource managers require accurate estimates of large herbivore abundance and demography to maintain ecological integrity. Common methods to count these species, including observations from low altitude helicopter flights, may conflict with other protected area management objectives and struggle to produce precise estimates for more cryptic species. To
Hanem G. Abouelezz, N. Thompson Hobbs
wiley   +1 more source

Abundance and occupancy trends of sooty grouse in western Oregon: determining best modeling practices by comparing observed and simulated data

Wildlife Biology, EarlyView.
Sooty grouse Dendragapus fuliginosus are large game birds that occupy montane forests in the Pacific Northwest, USA. These forests have been altered by human activities, which have been shown to have both positive and negative impacts on local populations.
Sarah J. K. Frey, Kelly M. Walton, Mikal L. Cline, Lindsey E. Sanders, Jonathan B. Dinkins   +4 more
wiley   +1 more source

A PMBM Filter for Tracking Coexisting Point and Group Targets with Target Spawning and Generalized Measurement Models

Remote Sensing
Accurate multi-target filtering is crucial for low-altitude surveillance, where point and group targets often coexist. Poisson multi-Bernoulli mixture (PMBM) filters provide a unified Bayesian framework for the joint filtering of point and group targets ...
Jichuan Zhang, Qi Jiang, Longxiang Jiao, Weidong Li, Cheng Hu   +4 more
doaj   +1 more source

Multi-Scan Implementation of the Trajectory Poisson Multi-Bernoulli Mixture Filter [PDF]

, 2019
Published in Journals of Advances in Information Fusion, Special issue on Multiple Hypothesis Tracking, Volume 14, Number 2, Page 213-235, December 2019.
Xia, Yuxuan, Granstrom, Karl, Svensson, Lennart, Garcia-Fernandez, Angel, Williams, Jason   +4 more
openaire   +2 more sources

A Poisson multi-Bernoulli mixture filter with spawning based on Kullback–Leibler divergence minimization

Chinese Journal of Aeronautics, 2021
Abstract In the classical form, the Poisson Multi-Bernoulli Mixture (PMBM) filter uses a PMBM density to describe target birth, surviving, and death, which does not model the appearance of spawned targets. Although such a model can handle target birth, surviving, and death well, its performance may degrade when target spawning arises.
Zhenzhen SU, Hongbing JI, Yongquan ZHANG
openaire   +1 more source

Rethinking Spatial Prioritisation for Primate Conservation in an Unprotected Intact Forest Landscape in the Gulf of Guinea

Animal Conservation, EarlyView.
This study highlights the importance of the unprotected Yabassi Key Biodiversity Area, Cameroon, for primate conservation in the Gulf of Guinea biodiversity hotspot. We modelled primate distribution patterns and found that historically overlooked parts of the landscape have high species richness and are critical for some threatened species.
Vianny Rodel Vouffo Nguimdo, Ekwoge Enang Abwe, Nelson Ekole Betobe, Bethan Jane Morgan, Matthias Waltert   +4 more
wiley   +1 more source

Innovative Filter for Nonlinear Multitarget Tracking: Improved SCKF-GM-DLPMBM Filter and Its Implementation

IEEE Access
The Poisson multi-Bernoulli mixture (PMBM) filter is capable of estimating the states of multiple targets based on available measurements. To address the limitations of the traditional PMBM filter, which involves the enumeration of assumptions that ...
Yubin Zhou, Bo Li, Jinyu Zhang, Zhikang Li   +3 more
doaj   +1 more source

Regularized reduced rank regression for mixed predictor and response variables

British Journal of Mathematical and Statistical Psychology, EarlyView.
Abstract In this paper, we introduce the Generalized Mixed Regularized Reduced Rank Regression model (GMR4), an extension of the GMR3 model designed to improve performance in high‐dimensional settings. GMR3 is a regression method for a mix of numeric, binary and ordinal response variables, while also allowing for mixed‐type predictors through optimal ...
Lorenza Cotugno, Mark de Rooij, Roberta Siciliano   +2 more
wiley   +1 more source

A joint model of cost and churn for the insurance industry

Journal of Risk and Insurance, EarlyView.
Abstract In insurance markets, claim costs are highly variable, heavy‐tailed, and difficult to predict. At the same time, policyholder retention and lapse behavior (customer churn) are critical determinants of long‐term profitability and solvency. Most existing models in the literature treat claim costs and lapses as independent, overlooking potential ...
Yumo Dong, Edward W. (Jed) Frees, Fei Huang, Francis K. C. Hui, Harald J. van Heerde   +4 more
wiley   +1 more source