In this work we propose a new supervised deformable model that generalizes the classical contour-based snake. This model is defined to deform in a feature space generated by a se...
This paper presents an empirical study for improving the performance of text chunking. We focus on two issues: the problem of selecting feature spaces, and the problem of alleviat...
In manipulating data such as in supervised learning, we often extract new features from original features for the purpose of reducing the dimensions of feature space and achieving ...
When using a Genetic Algorithm (GA) to optimize the feature space of pattern classification problems, the performance improvement is not only determined by the data set used, but a...
Zhijian Huang, Min Pei, Erik D. Goodman, Yong Huan...
Abstract. Finding point correspondences plays an important role in automatically building statistical shape models from a training set of 3D surfaces. For the point correspondence ...
Abstract. Good similarity functions are at the heart of effective case-based reasoning. However, the similarity functions that have been designed so far have been mostly linear, we...
The standard SVM formulation for binary classification is based on the Hinge loss function, where errors are considered not correlated. Due to this, local information in the featu...
Abstract. This paper presents our recent work on period disambiguation, the kernel problem in sentence boundary identification, with the maximum entropy (Maxent) model. A number o...
Multi-stream hidden Markov models (HMMs) have recently been very successful in audio-visual speech recognition, where the audio and visual streams are fused at the final decision...
In this work we propose an intuitive graphic framework for the effective visualization of MPEG-7 low-level features, in the context of classification and annotation of audio-visu...
Marco Campanella, Riccardo Leonardi, Pierangelo Mi...