AIMC Topic: Learning

Clear Filters Showing 621 to 630 of 1400 articles

Model architecture can transform catastrophic forgetting into positive transfer.

Scientific reports Jun 24, 2022
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...
Neural Networks, Computer Algorithms Learning
View on PubMed DOI

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

Computational intelligence and neuroscience Jun 24, 2022
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...
Humans Artificial Intelligence Learning Students Universities
View on PubMed DOI

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

PLoS computational biology Jun 21, 2022
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...
Neural Networks, Computer Learning Neuronal Plasticity Models, Neurological Neurons Synapses
View on PubMed DOI

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

Philosophical transactions. Series A, Mathematical, physical, and engineering sciences Jun 20, 2022
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...
Neural Networks, Computer Computer Simulation Learning
View on PubMed DOI

DPSSD: Dual-Path Single-Shot Detector.

Sensors (Basel, Switzerland) Jun 18, 2022
Object detection is one of the most important and challenging branches of computer vision. It has been widely used in people's lives, such as for surveillance security and autonomous driving. We propose a novel dual-path multi-scale object detection ...
Humans Neural Networks, Computer Algorithms Learning Disease Progression Automobile Driving
View on PubMed DOI

Learning disentangled representations in the imaging domain.

Medical image analysis Jun 17, 2022
Disentangled representation learning has been proposed as an approach to learning general representations even in the absence of, or with limited, supervision. A good general representation can be fine-tuned for new target tasks using modest amounts ...
Humans Machine Learning Software Learning
View on PubMed DOI

A Model for Analyzing Teaching Quality Data of Sports Faculties Based on Particle Swarm Optimization Neural Network.

Computational intelligence and neuroscience Jun 17, 2022
In this paper, we use a particle swarm optimization neural network algorithm to analyze the teaching data of physical education faculties and evaluate the quality of teaching in physical education faculties. By studying and analyzing the optimization...
Humans Neural Networks, Computer Algorithms Computer Simulation Learning Data Accuracy
View on PubMed DOI

A Low-Power Analog Processor-in-Memory-Based Convolutional Neural Network for Biosensor Applications.

Sensors (Basel, Switzerland) Jun 16, 2022
This paper presents an on-chip implementation of an analog processor-in-memory (PIM)-based convolutional neural network (CNN) in a biosensor. The operator was designed with low power to implement CNN as an on-chip device on the biosensor, which consi...
Neural Networks, Computer Learning Biosensing Techniques
View on PubMed DOI

Semisupervised Learning via Axiomatic Fuzzy Set Theory and SVM.

IEEE transactions on cybernetics Jun 16, 2022
In this article, we present a semantic semisupervised learning (Semantic SSL) approach targeted at unifying two machine-learning paradigms in a mutually beneficial way, where the classical support vector machine (SVM) learns to reveal primitive logic...
Algorithms Learning Support Vector Machine Supervised Machine Learning Semantics
View on PubMed DOI

ALSA: Adversarial Learning of Supervised Attentions for Visual Question Answering.

IEEE transactions on cybernetics Jun 16, 2022
Visual question answering (VQA) has gained increasing attention in both natural language processing and computer vision. The attention mechanism plays a crucial role in relating the question to meaningful image regions for answer inference. However, ...
Humans Machine Learning Algorithms Learning Natural Language Processing
View on PubMed DOI
Popular Topics
Recent Journals