Current approaches to image classification require training images prepared by hand. In this paper, we describe experiments on image classification using images gathered from the Web automatically as training images. To gather images from the Web, we use the probabilistic method we proposed before. In the method, we build a generative model which is based on the Gaussian mixture model (GMM) fro...

Population data provides statistical information that can in turn support decision making processes. It provides essential information regarding many practices such as rescue operations or humanitarian actions, which require the estimation of local population. While traditional approaches are possible, they tend to be time consuming and expensive. Copernicus Earth Observation data (Sentinel 2 s...

Introduction: A major problem facing the patients with chronic liver diseases is the diagnostic procedure.  The conventional diagnostic method depends mainly on needle biopsy which is an invasive method. There  are  some  approaches  to  develop  a  reliable  noninvasive  method  of  evaluating  histological  changes  in  sonograms. The main characteristic used to distinguish between the normal...

Conventional spectral-based classification methods have significant limitations in the digital classification of urban land-use and land-cover classes from high-resolution remotely sensed data because of the lack of consideration given to the spatial properties of images. To recognize the complex distribution of urban features in high-resolution image data, texture information consisting of a g...

A modified version of Boosted Mixture of Experts (BME) for low-resolution face recognition is presented in this paper. Most of the methods developed for low-resolution face recognition focused on improving the resolution of face images and/or special feature extraction methods that can deal effectively with low-resolution problem. However, we focused on the classification step of face recogniti...