AIMC Topic: Learning

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

Sensors (Basel, Switzerland) Apr 19, 2022
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...
Neural Networks, Computer Learning Lasers Algorithms
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The neural coding framework for learning generative models.

Nature communications Apr 19, 2022
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...
Brain Neurons Learning Neural Networks, Computer
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Memristor-based analogue computing for brain-inspired sound localization with in situ training.

Nature communications Apr 19, 2022
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...
Sound Localization Brain Neural Networks, Computer Neurons Learning Humans
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Online Course Model of Social and Political Education Using Deep Learning.

Computational intelligence and neuroscience Apr 19, 2022
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 ...
Thinking Reproducibility of Results Deep Learning Students Learning Male Female Humans
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Deep Reinforcement Learning for Resource Management on Network Slicing: A Survey.

Sensors (Basel, Switzerland) Apr 15, 2022
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...
Learning Algorithms Research Design Neural Networks, Computer
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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 Apr 13, 2022
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...
Child Attention Child, Preschool Learning Eye Movements Infant Humans Neural Networks, Computer
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Introducing principles of synaptic integration in the optimization of deep neural networks.

Nature communications Apr 7, 2022
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 ...
Learning Neuronal Plasticity Algorithms Brain Neural Networks, Computer
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Biased Pressure: Cyclic Reinforcement Learning Model for Intelligent Traffic Signal Control.

Sensors (Basel, Switzerland) Apr 6, 2022
Existing inefficient traffic signal plans are causing traffic congestions in many urban areas. In recent years, many deep reinforcement learning (RL) methods have been proposed to control traffic signals in real-time by interacting with the environme...
Learning Reward Machine Learning
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Efficient multitask learning with an embodied predictive model for door opening and entry with whole-body control.

Science robotics Apr 6, 2022
Robots need robust models to effectively perform tasks that humans do on a daily basis. These models often require substantial developmental costs to maintain because they need to be adjusted and adapted over time. Deep reinforcement learning is a po...
Robotics Motion Learning Reinforcement, Psychology Humans
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Critic Learning-Based Control for Robotic Manipulators With Prescribed Constraints.

IEEE transactions on cybernetics Apr 5, 2022
In this article, the optimal control problem for robotic manipulators (RMs) with prescribed constraints is addressed. Considering the environmental conditions and requirements of practical applications, prescribed constraints are imposed on the syste...
Robotics Learning Robotic Surgical Procedures
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