Información de la conferencia

BNNIO 2026: International Symposium on Biological Neural Networks and Intelligent Optimization

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Día de Entrega:
2025-12-13
Fecha de Notificación:
2025-12-18
Fecha de conferencia:
2026-01-16
Ubicación:
Zhuhai, China
Vistas: 2805   Seguidores: 0   Asistentes: 0

Solicitud de Artículos

BNNIO 2026 (International Symposium on Biological Neural Networks and Intelligent Optimization) is an academic conference held in Zhuhai, China on 2026-01-16. The paper submission deadline is 2025-12-13. Acceptance notifications are sent on 2025-12-18.

The topics of interest for submission include, but are not limited to: Artificial Intelligence Artificial intelligence Artificial neural network Deep learning Natural language processing Computer vision Knowledge graph construction Interpretable machine learning Embodied intelligence Neural Network Deep neural networks Convolutional neural networks Generative adversarial networks Recurrent neural networks Neural network structures Neural-symbolic hybrid models Explainability and visualisation methods for neural networks Neural networks in analysis and research in fields such as medicine, finance, and energy Biological Neural Networks Convolutional Neural Networks (CNN) in Image Processing Recurrent Neural Networks (RNN) and Their Applications in Sequence Data Autoencoders and Generative Models Neural Networks in Natural Language Processing (NLP) Neural Networks in Medical Image Analysis Neural Networks in Bioinformatics Neuronal Dynamics and Electrophysiological Properties Synaptic Plasticity Mechanisms and Learning Regulation Neural Circuit Structure and Functional Dynamics Brain-inspired neuromorphic computing and plasticity decoding Decoding of biological neural signals and brain-computer interfaces Intelligent Optimisation Evolutionary Algorithms Swarm Intelligence Machine Learning Reinforcement Learning Theory and Applications of Evolutionary Optimisation Algorithms Swarm Intelligence and Cooperative Optimisation Applications of Reinforcement Learning in Optimisation Problems Intelligent Heuristic and Meta-Heuristic Algorithm Design Research on the Interpretability and Robustness of Optimisation Algorithms
Última actualización por Dou Sun el

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