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ACL
2012
13 years 3 months ago
Fast and Robust Part-of-Speech Tagging Using Dynamic Model Selection
This paper presents a novel way of improving POS tagging on heterogeneous data. First, two separate models are trained (generalized and domain-specific) from the same data set by...
Jinho D. Choi, Martha Palmer
89
Voted
ICPR
2010
IEEE
14 years 10 months ago
Robust Foreground Object Segmentation via Adaptive Region-Based Background Modelling
We propose a region-based foreground object segmentation method capable of dealing with image sequences containing noise, illumination variations and dynamic backgrounds (as often...
Vikas Reddy, Conrad Sanderson, Brian C. Lovell
BMCBI
2010
171views more  BMCBI 2010»
15 years 24 days ago
PyMix - The Python mixture package - a tool for clustering of heterogeneous biological data
Background: Cluster analysis is an important technique for the exploratory analysis of biological data. Such data is often high-dimensional, inherently noisy and contains outliers...
Benjamin Georgi, Ivan Gesteira Costa, Alexander Sc...
NN
2004
Springer
102views Neural Networks» more  NN 2004»
15 years 6 months ago
A Quantitative Evaluation of a Bio-inspired Sound Segregation Technique for Two- and Three-Source Mixtures
A sound source separation technique based on a bio-inspired neural network, capable of functioning in more than two-source mixtures, is proposed. Separation results are compared wi...
Ramin Pichevar, Jean Rouat
CVPR
2012
IEEE
13 years 3 months ago
Robust Boltzmann Machines for recognition and denoising
While Boltzmann Machines have been successful at unsupervised learning and density modeling of images and speech data, they can be very sensitive to noise in the data. In this pap...
Yichuan Tang, Ruslan Salakhutdinov, Geoffrey E. Hi...