Dataset shift from the training data in a source domain to the data in a target domain poses a great challenge for many statistical learning methods. Most algorithms can be viewed ...
Recent progress in per-pixel object class labeling of natural images can be attributed to the use of multiple types of image features and sound statistical learning approaches. Wit...
Subspace learning techniques are widespread in pattern recognition research. They include Principal Component Analysis (PCA), Locality Preserving Projection (LPP), etc. These tech...
Abstract. Estimation of parameters of random field models from labeled training data is crucial for their good performance in many image analysis applications. In this paper, we p...
Abstract. Reliably extracting information from aerial imagery is a difficult problem with many practical applications. One specific case of this problem is the task of automatica...