Unsupervised data to content transformation with histogram-matching cycle-consistent generative adversarial networks

Stephan J. Ihle; Andreas M. Reichmuth; Sophie Girardin; Hana Han; Flurin Stauffer; Anne Bonnin; Marco Stampanoni; Karthik Pattisapu; János Vörös; Csaba Forró

doi:10.1038/s42256-019-0096-2

JOURNAL ARTICLE

Unsupervised data to content transformation with histogram-matching cycle-consistent generative adversarial networks

Stephan J. Ihle Andreas M. Reichmuth Sophie Girardin Hana Han Flurin Stauffer Anne Bonnin Marco Stampanoni Karthik Pattisapu János Vörös Csaba Forró

Year: 2019 Journal: Nature Machine Intelligence Vol: 1 (10)Pages: 461-470 Publisher: Nature Portfolio

DOI: 10.1038/s42256-019-0096-2

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Keywords:

Computer science Artificial intelligence Benchmark (surveying) Segmentation Machine learning Transformation (genetics) Set (abstract data type) Market segmentation Field (mathematics) Pattern recognition (psychology) Key (lock) Matching (statistics)

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Cell Image Analysis Techniques

Life Sciences → Biochemistry, Genetics and Molecular Biology → Biophysics

Generative Adversarial Networks and Image Synthesis

Physical Sciences → Computer Science → Computer Vision and Pattern Recognition

Image Processing Techniques and Applications

Physical Sciences → Engineering → Media Technology

Unsupervised data to content transformation with histogram-matching cycle-consistent generative adversarial networks

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