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Full-Text Articles in Engineering
Advantages Of Using Fuzzy Class Memberships In Self-Organizing Map And Support Vector Machines, Sunghwan Sohn, Cihan H. Dagli
Advantages Of Using Fuzzy Class Memberships In Self-Organizing Map And Support Vector Machines, Sunghwan Sohn, Cihan H. Dagli
Engineering Management and Systems Engineering Faculty Research & Creative Works
The self-organizing map (SOM) is naturally unsupervised learning, but if a class label is known, it can be used as the classifier. In a SOM classifier, each neuron is assigned a class label based on the maximum class frequency and classified by a nearest neighbor strategy. The drawback when using this strategy is that each pattern is treated by equal importance in counting class frequency regardless of its typicalness. For this reason, the fuzzy class membership can be used instead of crisp class frequency and this fuzzy membership-label neuron provides another perspective of a feature map. This fuzzy class membership …
A Hierarchical Classifier For Multispectral Satellite Imagery, Abdesselam Bouzerdoum
A Hierarchical Classifier For Multispectral Satellite Imagery, Abdesselam Bouzerdoum
Faculty of Engineering and Information Sciences - Papers: Part A
In this article, a hierarchical classifier is proposed for classification of ground-cover types of a satellite image of Kangaroo Island, South Australia. The image contains seven ground-cover types, which are categorized into three groups using principal component analysis. The first group contains clouds only, the second consists of sea and cloud shadow over land, and the third contains land and three types of forest. The sea and shadow over land classes are classified with 99% accuracy using a network of threshold logic units. The land and forest classes are classified by multilayer perceptrons (MLPs) using texture features and intensity values. …