Efficient Training of Convolutional Deep Belief Networks in the Frequency Domain for Application to High-Resolution 2D and 3D Images

DOI10.1162/NECO_a_00682zbMath1473.68177WikidataQ44673600 ScholiaQ44673600MaRDI QIDQ5380191

Tom Brosch, Roger Tam

Publication date: 4 June 2019

Published in: Neural Computation (Search for Journal in Brave)

zbMATH Keywords

frequency domainimage classificationconvolutional deep belief networks

Mathematics Subject Classification ID

Artificial neural networks and deep learning (68T07) Computing methodologies for image processing (68U10) Biomedical imaging and signal processing (92C55)

Related Items (1)

OAMIP: optimizing ANN architectures using mixed-integer programming

Uses Software

• darch
• ImageNet
• AlexNet

Cites Work

• Training Products of Experts by Minimizing Contrastive Divergence
• A Fast Learning Algorithm for Deep Belief Nets

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