We present a system that classifies pixels in a document image according to marking type such as machine print, handwriting, and noise. A segmenter module first splits an input ...
Many real-world classification applications fall into the class of positive and unlabeled (PU) learning problems. In many such applications, not only could the negative training ex...
The amount of text data on the Internet is growing at a very fast rate. Online text repositories for news agencies, digital libraries and other organizations currently store gigaan...
Abstract. Active learning refers to the task of devising a ranking function that, given a classifier trained from relatively few training examples, ranks a set of additional unlabe...
Object detection with a learned classifier has been applied successfully to difficult tasks such as detecting faces and pedestrians. Systems using this approach usually learn the ...