Hub
  • Software
  • Blog
  • Forum
  • Events
  • Documentation
  • About KNIME
  • KNIME Hub
  • knime
  • Spaces
  • Examples
  • 04_Analytics
  • 14_Deep_Learning
  • 02_Keras
  • 06_Semantic_Segmentation
WorkflowWorkflow

Semantic Segmentation with Deep Learning in KNIME

Deep learning Image processing Image analysis Computer vision Unet
+8

Last edited: 

Drag & drop
Like
Download workflow
Copy short link
Workflow preview
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. In order to run the example, please make sure you have the following KNIME extensions installed: * KNIME Deep Learning - Keras Integration (Labs) * KNIME Image Processing (Community Contributions Trusted) * KNIME Image Processing - Deep Learning Extension (Community Contributions Trusted) * KNIME Streaming Execution (Beta) (Labs) * KNIME Image Processing - Python Extension (Community Contributions Trusted) You also need a local Python installation that includes Keras. Please refer to https://www.knime.com/deeplearning#keras for installation recommendations and further information. Acknowledgements: The network architecture we use is an adaptation of the U-Net proposed in [1]. The dataset we used is taken from [2] [1] Ronneberger et al. in "U-Net: Convolutional Networks for Biomedical Image Segmentation" (https://arxiv.org/abs/1505.04597) [2] Gould et al. "Decomposing a Scene into Geometric and Semantically Consistent Regions." (http://dags.stanford.edu/projects/scenedataset.html)

External resources

  • Dataset website
  • U-Net paper

Used extensions & nodes

Created with KNIME Analytics Platform version 4.3.2
  • Go to item
    KNIME Base nodes Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.3.2

  • Go to item
    KNIME Deep Learning - Keras Integration Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.3.1

  • Go to item
    KNIME Image Processing Trusted extension

    University of Konstanz / KNIME

    Version 1.8.3

  • Go to item
    KNIME Javasnippet Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.3.0

  • Go to item
    KNIME Python Integration Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.3.1

  1. Go to item
  2. Go to item
  3. Go to item
  4. Go to item
  5. Go to item
  6. Go to item

Legal

By using or downloading the workflow, you agree to our terms and conditions.

Discussion
Discussions are currently not available, please try again later.

KNIME
Open for Innovation

KNIME AG
Hardturmstrasse 66
8005 Zurich, Switzerland
  • Software
  • Getting started
  • Documentation
  • E-Learning course
  • Solutions
  • KNIME Hub
  • KNIME Forum
  • Blog
  • Events
  • Partner
  • Developers
  • KNIME Home
  • KNIME Open Source Story
  • Careers
  • Contact us
Download KNIME Analytics Platform Read more on KNIME Server
© 2022 KNIME AG. All rights reserved.
  • Trademarks
  • Imprint
  • Privacy
  • Terms & Conditions
  • Credits