A regularized convolutional neural network for semantic image segmentation

DOI10.1142/S0219530519410148zbMath1462.68211arXiv1907.05287OpenAlexW3000277488WikidataQ126385149 ScholiaQ126385149MaRDI QIDQ5856266

Jun Liu, Fan Jia, Xue-Cheng Tai

Publication date: 25 March 2021

Published in: Analysis and Applications (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1907.05287

zbMATH Keywords

optimizationsemantic segmentationnetwork regularization

Mathematics Subject Classification ID

Artificial neural networks and deep learning (68T07) Applications of mathematical programming (90C90) Computing methodologies for image processing (68U10)

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Uses Software

• DeepLab
• OverFeat
• ImageNet
• SSD
• SegNet
• U-Net
• DeconvNet
• AlexNet
• PyDenseCRF

Cites Work

• Nonlinear total variation based noise removal algorithms
• Techniques for gradient-based bilevel optimization with non-smooth lower level problems
• Image recovery via total variation minimization and related problems
• An algorithm for total variation minimization and applications
• Augmented Lagrangian Method, Dual Methods, and Split Bregman Iteration for ROF, Vectorial TV, and High Order Models

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