Neural computation and self-organizing maps: an introduction
Neural computation and self-organizing maps: an introduction
Control and explanation in a signal understanding environment
Signal Processing - Intelligent systems for signal and image understanding
Semantic networks for understanding scenes
Semantic networks for understanding scenes
A Hybrid Approach to Signal Interpretation Using Neuronal and Semantic Networks
Mustererkennung 1993, Mustererkennung im Dienste der Gesundheit, 15. DAGM-Symposium
Neuronal, Statistisch, Wissensbasiert: Ein Beitrag zur Paradigmendiskussion für die Mustererkennung
Mustererkennung 1993, Mustererkennung im Dienste der Gesundheit, 15. DAGM-Symposium
A Neural 3-D Object Recognition Architecture Using Optimized Gabor Filters
ICPR '96 Proceedings of the International Conference on Pattern Recognition (ICPR '96) Volume IV-Volume 7472 - Volume 7472
Grammars and Discourse Theory to Describe and Recognize Mechanical Assemblies
Proceedings of the Joint IAPR International Workshops on Advances in Pattern Recognition
Structure and Process: Learning of Visual Models and Construction Plans for Complex Objects
Revised Papers from the International Workshop on Sensor Based Intelligent Robots
Evaluating Integrated Speech- and Image Understanding
ICMI '02 Proceedings of the 4th IEEE International Conference on Multimodal Interfaces
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We present a hybrid approach attaching probabilistic formalisms, as artificial neural networks or hidden Markov models, to concepts of a semantic network for a robust and efficient detection of objects. Additionally, an efficient processing strategy for image sequences is outlined which propagates the structural results of the semantic network as an expectation for the next image. This method allows to produce linked results over time supporting the recognition of events and actions.