Results 161 to 170 of about 39,740 (209)

Physical crowding truncates intrinsic Lévy-like motility into caste-specific movement regimes in social termites. [PDF]

Mov Ecol
Bai ZD, Han JX, Ye N, Wang C, Sillam-Dussès D, Wang RW.   +5 more
europepmc   +1 more source

Development of an artificial intelligence model to identify duodenal polyps in patients with familial adenomatous polyposis. [PDF]

IGIE
Schupack D, Sood S, Fetzer J, Shalini S, Arunachalam SP, League JB, Leggett C, Boardman L, Coelho-Prabhu N.   +8 more
europepmc   +1 more source

Inherent Leakage of Hydrophobic Gating in BK Channels. [PDF]

PRX Life
Jia Z, Chen J.
europepmc   +1 more source

A fixed methane filter maximizes freshwater emissions under warming. [PDF]

Nat Clim Chang
Harpenslager SF, Randall K, Zhu Y, Jackson MC, Sanders I, Gallo B, Harris D, Prentice H, Bespalaya YV, Aksenova OV, Milner A, Cameron TC, McKew BA, O'Gorman EJ, Yvon-Durocher G, Friberg N, Purdy KJ, Woodward G, Dumbrell AJ, Trimmer M.   +19 more
europepmc   +1 more source

Changes in visuocortical engagement and oscillatory brain activity during associative learning. [PDF]

Sci Rep
Gardy SM, Panitz C, Engle H, Gilbert F, Keil A.   +4 more
europepmc   +1 more source

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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

Multiple model spline probability hypothesis density filter

IEEE Transactions on Aerospace and Electronic Systems, 2016
The probability hypothesis density (PHD) filter is an efficient algorithm for multitarget tracking in the presence of nonlinearities and/or non-Gaussian noise. The sequential Monte Carlo (SMC) and Gaussian mixture (GM) techniques are commonly used to implement the PHD filter.
Rajiv Sithiravel, Bhashyam Balaji, Thiagalingam Kirubarajan   +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

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