Nonlocal regularized CNN for image segmentation

DOI10.3934/IPI.2020041zbMath1451.68307OpenAlexW3042143729MaRDI QIDQ2198002

Jun Liu, Fan Jia, Xue-Cheng Tai

Publication date: 1 September 2020

Published in: Inverse Problems and Imaging (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.3934/ipi.2020041

zbMATH Keywords

regularizationdualityimage segmentationnonlocal total variationconvolutional neural networkCNN

Mathematics Subject Classification ID

Computing methodologies for image processing (68U10) Numerical methods based on nonlinear programming (49M37)

Related Items (3)

Proximal gradient methods for general smooth graph total variation model in unsupervised learning ⋮ Weighted area constraints-based breast lesion segmentation in ultrasound image analysis ⋮ A Weighted Difference of Anisotropic and Isotropic Total Variation for Relaxed Mumford--Shah Color and Multiphase Image Segmentation

Uses Software

• ImageNet
• SegNet
• U-Net
• DeconvNet
• AlexNet
• PyDenseCRF

Cites Work

• Nonlinear total variation based noise removal algorithms
• A unifying approach to isotropic and anisotropic total variation denoising models
• Constraints on deformable models: Recovering 3D shape and nonrigid motion
• An effective region force for some variational models for learning and clustering
• New region force for variational models in image segmentation and high dimensional data clustering
• Higher-order TV methods -- enhancement via Bregman iteration
• Optimal approximations by piecewise smooth functions and associated variational problems
• Nonlocal Operators with Applications to Image Processing
• Noise removal using fourth-order partial differential equation with applications to medical magnetic resonance images in space and time

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