Results 201 to 210 of about 175,081 (248)

Reliability Assessment of Harmonic Reducers Based on the Two-Phase Hybrid Stochastic Degradation Process. [PDF]

Sensors (Basel)
Wei L, Liu P, Tian H, Li H, Qiu Y.
europepmc   +1 more source

Comparative Evidence-Based Model Choice: A Sketch of a Theory. [PDF]

Entropy (Basel)
Bandyopadhyay PS, Shetty S, Brittan G.
europepmc   +1 more source

Balancing conflict and coexistence: Interactions between invasive monk parakeets and native urban birds. [PDF]

Ecol Appl
Blanco-González J, López-Rull I, Enríquez F, Cayuela L.   +3 more
europepmc   +1 more source

A Genetic Algorithm-Optimized Kernel Density Estimation and D-S Evidence Fusion Classification for Predicting the Stability of Double Perovskite Materials. [PDF]

Materials (Basel)
Liang G, Zhang J.
europepmc   +1 more source

Bayesian Evaluation of Treatment Effect of Avelumab Plus Axitinib for Advanced Renal Cell Carcinoma. [PDF]

Cancer Med
Fukuokaya W, Mori K, Yanagisawa T, Ito K, Imai Y, Urabe F, Rajwa P, Shariat SF, Kimura T, Hirakawa A.   +9 more
europepmc   +1 more source

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Forward-Backward Probability Hypothesis Density Smoothing

IEEE Transactions on Aerospace and Electronic Systems, 2012
A forward-backward probability hypothesis density (PHD) smoother involving forward filtering followed by backward smoothing is proposed. The forward filtering is performed by Mahler's PHD recursion. The PHD backward smoothing recursion is derived using finite set statistics (FISST) and standard point process theory.
Ronald P S Mahler, Ba-Tuong Võ, Ba-Ngu Võ   +2 more
exaly   +3 more sources

Analytic Implementations of the Cardinalized Probability Hypothesis Density Filter

IEEE Transactions on Signal Processing, 2007
The probability hypothesis density (PHD) recursion propagates the posterior intensity of the random finite set (RFS) of targets in time. The cardinalized PHD (CPHD) recursion is a generalization of the PHD recursion, which jointly propagates the posterior intensity and the posterior cardinality distribution.
Ba-Tuong Võ, Ba-Ngu Võ, Antonio Cantoni   +2 more
exaly   +2 more sources

Data-Driven Probability Hypothesis Density Filter for Visual Tracking

IEEE Transactions on Circuits and Systems for Video Technology, 2008
We apply the probability hypothesis density (PHD) filter to track a random number of pedestrians in image sequences. The PHD filter is implemented using particle filter. How to design importance functions of the particle PHD filter remains a challenge, especially when targets can appear, disappear, merge, or split at any time.
Jian-Kang Wu, Ashraf A Kassim
exaly   +2 more sources

Probability hypothesis density filter with uncertainty in the probability of detection

Advances in Space Research, 2021
Abstract The space around the earth is becoming increasingly populated. Efficient tracking algorithms are hence integral to protect active space assets from collisions. Ground-based measurements are the primary source of information for any tracking algorithm.
Rohith Reddy Sanaga, Carolin Frueh
openaire   +1 more source

The spline probability hypothesis density filter

SPIE Proceedings, 2012
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Rajiv Sithiravel, Xin Chen, Ratnasingham Tharmarasa, Bhashyam Balaji, Thiagalingam Kirubarajan   +4 more
openaire   +2 more sources