ICASSP
2011
IEEE
12 years 8 months ago
2011
IEEE
In this paper, models and algorithms are presented for transcription of pitch and timings in polyphonic music extracts, focusing on the algorithm details of the sequential Markov ...
ICASSP
2011
IEEE
12 years 8 months ago
2011
IEEE
This paper studies a variational Bayesian unmixing algorithm for hyperspectral images based on the standard linear mixing model. Each pixel of the image is modeled as a linear com...
ICASSP
2011
IEEE
12 years 8 months ago
2011
IEEE
Signals in response to time-localized events of a common phenomenon tend to exhibit a common shape, but with variable time scale, amplitude, and delay across trials in many domain...
ICASSP
2011
IEEE
12 years 8 months ago
2011
IEEE
We briefly present the current state-of-the-art approaches for group and extended object tracking with an emphasis on particle methods which have high potential to handle complex...
TIP
2010
12 years 11 months ago
2010
Lidar waveforms are 1D signals representing a train of echoes caused by reflections at different targets. Modeling these echoes with the appropriate parametric function is useful ...
TIP
2010
12 years 11 months ago
2010
We propose to model the image differentials of astrophysical source maps by Student's t-distribution and to use them in the Bayesian source separation method as priors. We int...
TCBB
2010
12 years 11 months ago
2010
Markov chain Monte Carlo has been the standard technique for inferring the posterior distribution of genome rearrangement scenarios under a Bayesian approach. We present here a neg...
SAC
2010
ACM
12 years 11 months ago
2010
ACM
The label switching problem is caused by the likelihood of a Bayesian mixture model being invariant to permutations of the labels. The permutation can change multiple times betwee...
PAMI
2010
12 years 11 months ago
2010
We present a new approach for building reconstruction from a single Digital Surface Model (DSM). It treats buildings as an assemblage of simple urban structures extracted from a li...
JMLR
2010
12 years 11 months ago
2010
Markov Random Fields (MRFs) are an important class of probabilistic models which are used for density estimation, classification, denoising, and for constructing Deep Belief Netwo...