AI Medical Compendium Topic:
Learning

Clear Filters Showing 601 to 610 of 1362 articles

More than surgical tools: a systematic review of robots as didactic tools for the education of professionals in health sciences.

Advances in health sciences education : theory and practice
Within the field of robots in medical education, most of the work done during the last years has focused on surgeon training in robotic surgery, practicing surgery procedures through simulators. Apart from surgical education, robots have also been wi...

Analysis on the Reform and Development of Physical Education Services in the Context of 5G Connected Communication.

Computational intelligence and neuroscience
With the continuous growth of science and technology, mankind has entered the fifth-generation (5G) era. In this background, the development of many fields will face great opportunities and challenges, including the field of physical education (PE). ...

SIRe-Networks: Convolutional neural networks architectural extension for information preservation via skip/residual connections and interlaced auto-encoders.

Neural networks : the official journal of the International Neural Network Society
Improving existing neural network architectures can involve several design choices such as manipulating the loss functions, employing a diverse learning strategy, exploiting gradient evolution at training time, optimizing the network hyper-parameters...

Learning in deep neural networks and brains with similarity-weighted interleaved learning.

Proceedings of the National Academy of Sciences of the United States of America
Understanding how the brain learns throughout a lifetime remains a long-standing challenge. In artificial neural networks (ANNs), incorporating novel information too rapidly results in catastrophic interference, i.e., abrupt loss of previously acquir...

Predicting Students' Academic Performance with Conditional Generative Adversarial Network and Deep SVM.

Sensors (Basel, Switzerland)
The availability of educational data obtained by technology-assisted learning platforms can potentially be used to mine student behavior in order to address their problems and enhance the learning process. Educational data mining provides insights fo...

Sharing Rewards Undermines Coordinated Hunting.

Journal of computational biology : a journal of computational molecular cell biology
Coordinated hunting is widely observed in animals, and sharing rewards is often considered a major incentive for its success. While current theories about the role played by sharing in coordinated hunting are based on correlational evidence, we revea...

Model architecture can transform catastrophic forgetting into positive transfer.

Scientific reports
The work of McCloskey and Cohen popularized the concept of catastrophic interference. They used a neural network that tried to learn addition using two groups of examples as two different tasks. In their case, learning the second task rapidly deterio...

College English Reading Teaching Integrating Production Oriented Approach from the Perspective of Artificial Intelligence.

Computational intelligence and neuroscience
The objectives are to solve many problems in traditional English reading teaching, such as the passive acceptance of students' learning situation, the rigid teaching mode of teachers and the difficulty in taking into account the individual needs of e...

Sequence learning, prediction, and replay in networks of spiking neurons.

PLoS computational biology
Sequence learning, prediction and replay have been proposed to constitute the universal computations performed by the neocortex. The Hierarchical Temporal Memory (HTM) algorithm realizes these forms of computation. It learns sequences in an unsupervi...

GFINNs: GENERIC formalism informed neural networks for deterministic and stochastic dynamical systems.

Philosophical transactions. Series A, Mathematical, physical, and engineering sciences
We propose the GENERIC formalism informed neural networks (GFINNs) that obey the symmetric degeneracy conditions of the GENERIC formalism. GFINNs comprise two modules, each of which contains two components. We model each component using a neural netw...