In this paper we present an innovative two-stage adaptation approach for handwriting recognition that is based on clustering of similar pages in the training data. In our approach...
Logical entity recognition in heterogeneous collections of document page images remains a challenging problem since the performance of traditional supervised methods degrade drama...
In this paper a writer-independent on-line handwriting recognition system is described comparing the influence of handwriting normalization and adaptation techniques on the recogn...
We present Cluster Onset Detection (COD), a novel algorithm to aid in detection of epidemic outbreaks. COD employs unsupervised learning techniques in an online setting to partiti...
A good distance metric is crucial for many data mining tasks. To learn a metric in the unsupervised setting, most metric learning algorithms project observed data to a lowdimensio...