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Semantic Segmentation with Deep Learning in KNIME

Deep learning Image processing Image analysis Computer vision Unet
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Benjamin Wilhelm profile image

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This workflow shows how the new KNIME Keras integration can be used to train and deploy a specialized deep neural network for semantic segmentation. This means that our network decides for each pixel in the input image, what class of object it belongs to.

Used extensions & nodes

Created with KNIME Analytics Platform version 4.5.2
  • KNIME Base nodes Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.5.2

    knime
  • KNIME Basic File System Connectors Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.5.2

    knime
  • KNIME Deep Learning - Keras Integration Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.5.0

    knime
  • KNIME Deep Learning - TensorFlow Integration Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.5.0

    knime
  • KNIME Image Processing Trusted extension

    University of Konstanz / KNIME

    Version 1.8.3

    bioml-konstanz
  • KNIME Javasnippet Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.5.0

    knime
  • KNIME Python Integration Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.5.2

    knime
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