Abstract. This paper investigates a new extension of the Probabilistic Latent Semantic Analysis (PLSA) model [6] for text classification where the training set is partially labeled...
We present some greedy learning algorithms for building sparse nonlinear regression and classification models from observational data using Mercer kernels. Our objective is to dev...
Prasanth B. Nair, Arindam Choudhury 0002, Andy J. ...
In this paper, we introduce a rotational invariant feature set for texture segmentation and classification, based on an extension of fractal dimension (FD) features. The FD extract...
We consider the problem of distributed classification of multiple observations of the same object that are collected in an ad-hoc network of vision sensors. Assuming that each sen...
We propose a scene classification method, which combines two popular methods in the literature: Spatial Pyramid Matching (SPM) and probabilistic Latent Semantic Analysis (pLSA) mod...