AIMC Topic: Learning

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Design and Implementation of Tourism Teaching System Based on Artificial Intelligence Technology.

Computational intelligence and neuroscience
The tourism teaching system provides all kinds of teaching resources for students and shares good teachers, which greatly improves the quality of teaching and learning, and it enables students to teach and learn randomly in the system. The mode of ed...

Training of artificial neural networks with the multi-population based artifical bee colony algorithm.

Network (Bristol, England)
Nowadays, artificial intelligence has gained recognition in every aspect of life. Artificial neural networks, one of the most efficient artificial intelligence techniques, is remarkably successful in computers' acquisition of the learning and interpr...

Attributed graph clustering with multi-task embedding learning.

Neural networks : the official journal of the International Neural Network Society
Attributed graph clustering is challenging as it needs to effectively combine both graph structure and node feature information to accomplish node clustering. Recent studies mostly adopt graph neural networks to learn node embeddings, then apply trad...

Seabed Modelling by Means of Airborne Laser Bathymetry Data and Imbalanced Learning for Offshore Mapping.

Sensors (Basel, Switzerland)
An important problem associated with the aerial mapping of the seabed is the precise classification of point clouds characterizing the water surface, bottom, and bottom objects. This study aimed to improve the accuracy of classification by addressing...

The neural coding framework for learning generative models.

Nature communications
Neural generative models can be used to learn complex probability distributions from data, to sample from them, and to produce probability density estimates. We propose a computational framework for developing neural generative models inspired by the...

Memristor-based analogue computing for brain-inspired sound localization with in situ training.

Nature communications
The human nervous system senses the physical world in an analogue but efficient way. As a crucial ability of the human brain, sound localization is a representative analogue computing task and often employed in virtual auditory systems. Different fro...

Online Course Model of Social and Political Education Using Deep Learning.

Computational intelligence and neuroscience
This study aims to improve the social and political literacy of college students. Social and Political Education (SPE) is studied for undergraduates. Firstly, the background of the subject research is introduced. The face recognition module is built ...

Deep Reinforcement Learning for Resource Management on Network Slicing: A Survey.

Sensors (Basel, Switzerland)
Network Slicing and Deep Reinforcement Learning (DRL) are vital enablers for achieving 5G and 6G networks. A 5G/6G network can comprise various network slices from unique or multiple tenants. Network providers need to perform intelligent and efficien...

iCatcher: A neural network approach for automated coding of young children's eye movements.

Infancy : the official journal of the International Society on Infant Studies
Infants' looking behaviors are often used for measuring attention, real-time processing, and learning-often using low-resolution videos. Despite the ubiquity of gaze-related methods in developmental science, current analysis techniques usually involv...

Introducing principles of synaptic integration in the optimization of deep neural networks.

Nature communications
Plasticity circuits in the brain are known to be influenced by the distribution of the synaptic weights through the mechanisms of synaptic integration and local regulation of synaptic strength. However, the complex interplay of stimulation-dependent ...