ARIADNE: pattern-directed inference and hierarchical abstraction in protein structure recognition
Communications of the ACM
Markov random field models in computer vision
ECCV '94 Proceedings of the third European conference on Computer Vision (Vol. II)
Neural Networks for Pattern Recognition
Neural Networks for Pattern Recognition
Learning Logical Definitions from Relations
Machine Learning
Logical Structure Recognition of Scientific Bibliographic References
ICDAR '97 Proceedings of the 4th International Conference on Document Analysis and Recognition
Pattern recognition algorithms based on space-filling curves and orthogonal expansions
IEEE Transactions on Information Theory
IEEE Transactions on Neural Networks
On the construction and training of reformulated radial basis function neural networks
IEEE Transactions on Neural Networks
Hi-index | 0.00 |
Our aim is to discuss problems of structure recognition in the Bayesian setting, treating structures as special cases of relations. We start from a general problem statement, which is solvable by dynamic programming for linear structures. Then, we consider splitting the problem of structure recognition into a series of pairwise relations testing, which is applicable when on-line processing of intensive data streams is necessary. An appropriate neural network structure is also proposed and tested on a video stream.