Design anomalies, introduced during software evolution, are frequent causes of low maintainability and low flexibility to future changes. Because of the required knowledge, an im...
The objective of this paper is to study the existing methods for unsupervised object recognition and image categorization and propose a model that can learn directly from the outp...
Background: Clustering the information content of large high-dimensional gene expression datasets has widespread application in "omics" biology. Unfortunately, the under...
In this paper, we study the problem of transfer learning from text to images in the context of network data in which link based bridges are available to transfer the knowledge bet...
This paper discusses the problem of knowledge discovery in image databases with particular focus on the issues which arise when absolute ground truth is not available. It is often...
Padhraic Smyth, Michael C. Burl, Usama M. Fayyad, ...