Багатошарова МГУА-нейро-фаззі мережа на основі розширених нечітких нейронів та її використання для онлайн разпізнавання виразів обличчя
Real-time image recognition is required in many important practical problems. Interaction with users in online mode requires flexibility and adaptability from applications. The Group Method of Data Handling (GMDH) allows changing the model structure and adjusting the system architecture to the chara...
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| Datum: | 2020 |
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| Hauptverfasser: | , , , |
| Format: | Artikel |
| Sprache: | Englisch |
| Veröffentlicht: |
The National Technical University of Ukraine "Igor Sikorsky Kyiv Polytechnic Institute"
2020
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| Schlagworte: | |
| Online Zugang: | http://journal.iasa.kpi.ua/article/view/221271 |
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| Назва журналу: | System research and information technologies |
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System research and information technologies| Zusammenfassung: | Real-time image recognition is required in many important practical problems. Interaction with users in online mode requires flexibility and adaptability from applications. The Group Method of Data Handling (GMDH) allows changing the model structure and adjusting the system architecture to the characteristics of each task under consideration. Moreover, the approximating properties of neo-fuzzy neurons used as elements of the system provide the high recognition accuracy under conditions of short data samples. This paper proposes a multilayer GMDH-neuro-fuzzy network based on extended neo-fuzzy neurons. The learning algorithm has filtering and tracking properties, guarantees the required speed important for real-time applications. The effectiveness of the proposed system is confirmed for the human emotions recognition. |
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