An inference implementation based on extended weighted finite automata
ACSC '01 Proceedings of the 24th Australasian conference on Computer science
Similarity Enrichment in Image Compression through Weighted Finite Automata
COCOON '00 Proceedings of the 6th Annual International Conference on Computing and Combinatorics
Unification and extension of weighted finite automata applicable to image compression
Theoretical Computer Science
Epileptic Spike Recognition in Electroencephalogram Using Deterministic Finite Automata
Journal of Medical Systems
Weighted Finite Automata encoding over Thai language
Proceedings of the 2nd International Conference on Interaction Sciences: Information Technology, Culture and Human
On generalizations of weighted finite automata and graphics applications
CAI'07 Proceedings of the 2nd international conference on Algebraic informatics
DFAspike: A new computational proposition for efficient recognition of epileptic spike in EEG
Computers in Biology and Medicine
Ancient typefaces and parametric weighted finite automata
Rainbow of computer science
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Weighted finite automata (WFA) exploit self-similarities within single pictures and also sequences of pictures to remove spatial and temporal redundancies. Their implementation then combines techniques from hierarchical methods related to quadtrees and from vector quantization to achieve performance results for low bit rates which can be put on a par with state-of-the-art codecs like embedded zero-tree wavelet coding. Due to their simple mathematical structure, WFA provide an ideal platform for efficient hybrid compression methods. Therefore, WFA were chosen as a starting point for a fractal-like video compression integrating a hierarchical motion compensation as well as an option to vary the compression quality between “centers of interest” and “background” in a flexible manner