U-Net: Convolutional Networks for Biomedical Image Segmentation

Olaf Ronneberger; Philipp Fischer; Thomas Brox

doi:10.1007/978-3-319-24574-4_28

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U-Net: Convolutional Networks for Biomedical Image Segmentation

Olaf Ronneberger Philipp Fischer Thomas Brox

Year: 2015 Lecture notes in computer science Pages: 234-241 Publisher: Springer Science+Business Media

DOI: 10.1007/978-3-319-24574-4_28

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Keywords:

Computer science Artificial intelligence Segmentation Margin (machine learning) Sliding window protocol Context (archaeology) Path (computing) Image segmentation Pattern recognition (psychology) Network architecture Image (mathematics) Window (computing) Convolutional neural network Computer vision Machine learning Computer network

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Cell Image Analysis Techniques

Life Sciences → Biochemistry, Genetics and Molecular Biology → Biophysics

Advanced Neural Network Applications

Physical Sciences → Computer Science → Computer Vision and Pattern Recognition

Image Processing Techniques and Applications

Physical Sciences → Engineering → Media Technology

U-Net: Convolutional Networks for Biomedical Image Segmentation

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