One-Class Classification for Mapping a Specific Land-Cover Class: SVDD Classification of Fenland

Sanchez-Hernandez, Carolina and Boyd, Doreen S. and Foody, Giles M. (2007) One-class classification for monitoring a specific land cover class: SVDD classification of fenland. IEEE Transactions

Remote sensing is a major source of land cover information. Commonly, interest focuses on a single land cover class. Although a conventional multi-class classifier may be used to provide a map depicting the class of interest the analysis is not focused on that class and may be sub-optimal in terms of the accuracy of its classification. With a conventional classifier, considerable effort is dire...

Spatial Classification for Land Cover Mapping

Zhe Jiang, [email protected] Abstract: My research explores novel computational techniques to map the physical cover (e.g., forests) of the earth’s surface from satellite images. Processing these images is labor-intensive and a significant burden on scientists. Existing methods ignore spatial information and assume that pixels are statistically independent. Consequently, they produce erroneous map...

Self-Learning Based Land-Cover Classification Using Sequential Class Patterns from Past Land-Cover Maps

To improve the accuracy of classification with a small amount of training data, this paper presents a self-learning approach that defines class labels from sequential patterns using a series of past land-cover maps. By stacking past land-cover maps, unique sequence rule information from sequential change patterns of land-covers is first generated, and a rule-based class label image is then prep...

Classification Using Class Cover Catch Digraphs

One-Class SVMs for Document Classification

We implemented versions of the SVM appropriate for one-class classification in the context of information retrieval. The experiments were conducted on the standard Reuters data set. For the SVM implementation we used both a version of Schölkopf et al. and a somewhat different version of one-class SVM based on identifying “outlier” data as representative of the second-class. We report on experim...