Unsupervised learning and continual learning in neural networks

Unsupervised learning and continual learning in neural networks

<p>For decades research has pursued the ambitious goal of designing computer models that learn to solve problems as effectively as humans can. Artificial neural networks -- generic, optimizable models that were originally inspired by biological neurons in the brain -- appear to provide a promi...

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Bibliografiske detaljer
Hovedforfatter:	Ji, X
Andre forfattere:	Vedaldi, A
Format:	Thesis
Sprog:	English
Udgivet:	2021
Fag:	Artificial intelligence Neural networks (Computer science) Computer vision

Lignende værker

Unsupervised learning procedures for neural networks /
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Unsupervised point cloud representation learning with deep neural networks: a survey
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Artificial neural networks /
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Neural network design and the complexity of learning /
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Artificial neural network - ICANN 97 /
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Recent Advances in Artificial Neural Networks /
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A study of backpropagation and particle swarm optimization learning methods for artificial neural network training /
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Hybrid committee artificial neural networks for classification of banana maturity level /
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Hybrid committee artificial neural networks for classification of banana maturity level [electronic resource] /
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Udgivet: (2006)

Non-probabilistic artificial neural network incorporating uncertainties in vibration based damage detection /
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Regional Multi-Scale Approach for Visually Pleasing Explanations of Deep Neural Networks
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Unsupervised learning of clutter-resistant visual representations from natural videos
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Non-probabilistic artificial neural network incorporating uncertainties in vibration based damage detection [electronic resource] /
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Attack on prediction confidence of deep learning neural networks
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Udgivet: (2022)

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Error-correcting output codes with ensemble diversity for robust learning in neural networks
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Object classification using deep learning /
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Artificial Neural Networks - ICANN 2007 [electronic resource] : 17th International Conference, Porto, Portugal, September 9-13, 2007: Proceedings, Part II /
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Modelling of biogas production process with evolutionary artificial neural network and genetic algorithm
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Udgivet: (2017)

Object classification using deep learning [electronic resource] /
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Udgivet: (2015)

Weed Density and Distribution Estimation for Precision Agriculture Using Semi-Supervised Learning
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Udgivet: (2021-01-01)

Neural Network Preference Learning Approaches For Improving Agent-Based Meeting Scheduling Problems
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Udgivet: (2007)

Review and analysis of deep neural network models for Alzheimer's disease classification using brain medical resonance imaging
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Understanding convolutional neural networks
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Udgivet: (2020)

Artificial intelligence and neural networks : 14th Turkish symposium, TAINN 2005, Izmir, Turkey, June 16-17, 2005 : revised selected papers /
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Udgivet: (2006)

Celiac Disease Deep Learning Image Classification Using Convolutional Neural Networks
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Udgivet: (2024-08-01)

Disrupted visual input unveils the computational details of artificial neural networks for face perception
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Udgivet: (2022-11-01)

Subspace learning of neural networks /
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Federated learning for graph neural networks
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Udgivet: (2023)

Adaptive memory networks with self-supervised learning for unsupervised anomaly detection
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Three-term back propagation neural network for moisture prediction /
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Trends in neural computation /
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Udgivet: (2007)

Matching sensor ontologies with unsupervised neural network with competitive learning
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Udgivet: (2021-11-01)