We consider the problem of PAC-learning distributions over strings, represented by probabilistic deterministic finite automata (PDFAs). PDFAs are a probabilistic model for the gen...
Recognition and encoding of digitized historical documents is still a challenging and difficult task. A major problem is the occurrence of unknown glyphs and symbols which might n...
We describe a new corpus collected for comparative evaluation of OCR-software and postcorrection techniques. The corpus is freely available for academic groups and use. The major ...
Stoyan Mihov, Klaus U. Schulz, Christoph Ringlstet...
The work proposes a hierarchical architecture for learning amic scenes at various levels of knowledge abstraction. The raw visual information is processed at different stages to g...
We introduce a new class of Reinforcement Learning algorithms designed to operate in perceptual spaces containing images. They work by classifying the percepts using a computer vi...