Statistical Pattern Recognition: A Review
IEEE Transactions on Pattern Analysis and Machine Intelligence
Clustering and Classification in Structured Data Domains Using Fuzzy Lattice Neurocomputing (FLN)
IEEE Transactions on Knowledge and Data Engineering
Kolmogorov Complexity of Finite Sequences and Recognition of Different Preictal EEG Patterns
CBMS '95 Proceedings of the Eighth Annual IEEE Symposium on Computer-Based Medical Systems
The Journal of Machine Learning Research
EEG signal classification using wavelet feature extraction and a mixture of expert model
Expert Systems with Applications: An International Journal
Semantic-based facial expression recognition using analytical hierarchy process
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
EURASIP Journal on Advances in Signal Processing
Expert Systems with Applications: An International Journal
Review: Neural networks and statistical techniques: A review of applications
Expert Systems with Applications: An International Journal
An efficient classifier to diagnose of schizophrenia based on the EEG signals
Expert Systems with Applications: An International Journal
Nonparametric classification based on local mean and class statistics
Expert Systems with Applications: An International Journal
An intelligent strategy for the automatic detection of highlights in tennis video recordings
Expert Systems with Applications: An International Journal
Swarm optimized organizing map (SWOM): A swarm intelligence basedoptimization of self-organizing map
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Effective content-based video retrieval using pattern-indexing and matching techniques
Expert Systems with Applications: An International Journal
Hi-index | 12.05 |
The current paper focuses on the implementation of hybrid expert systems for audiovisual content description and management, by means of pattern analysis. The proposed methodology combines audio detection-segmentation, surveillance-video motion-detection and hierarchical audio pattern recognition, using neural networks, statistical clustering and syntactic pattern classification. The associated, video-assisted, bioacoustics application focuses on Abdominal Sounds (AS) pattern classification, promising to deliver new potentials in non-invasive Gastro-Intestinal Motility (GIM) monitoring. The current work introduces new techniques for content analysis automation of prolonged multi-channel recordings, facilitating automated GIM auscultation analysis. Thus, it seeks for the establishment of novel diagnostic tools over functional GIM disorders, with the advantage that subjects' behavior and related psycho-physiological issues can be monitored to further analyze their dependencies. Qualitative and quantitative analysis validated the soundness of the adopted pattern classification taxonomy, resulting remarkable pattern recognition accuracy. Based on preliminary results, the proposed methodology can be successfully applied to general audiovisual content classification, description and management tasks (besides bioacoustics).