Hub
Pricing About
WorkflowWorkflow

Edit MNIST SavedModel

Deep learningTensorFlowImage classification
knime profile image
Draft Latest edits on 
Jun 25, 2018 2:23 PM
Drag & drop
Like
Download workflow
Workflow preview
This workflow shows how to edit a TensorFlow model using the TensorFlow Python API by adding an additional output to a model. The loaded model does classification on MNIST but only outputs the probabilities for each class. We edit the model such that it outputs the class as well. In order to run the example, please make sure you have the following KNIME extensions installed: * KNIME Deep Learning - TensorFlow Integration (Labs) * KNIME Image Processing (Community Contributions Trusted) * KNIME Image Processing - Deep Learning Extension (Community Contributions Trusted) Acknowledgements: The architecture of the used network was taken but slightly changed from https://www.tensorflow.org/tutorials/layers. The enclosed pictures are from the MNIST dataset (http://yann.lecun.com/exdb/mnist/) [1]. [1] Y. LeCun, L. Bottou, Y. Bengio, and P. Haffner. "Gradient-based learning applied to document recognition." Proceedings of the IEEE, 86(11):2278-2324, November 1998.
Loading deploymentsLoading ad hoc jobs

Used extensions & nodes

Created with KNIME Analytics Platform version 4.1.0
  • Go to item
    KNIME CoreTrusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.1.0

    knime profile image
    knime
  • Go to item
    KNIME Deep Learning - Keras IntegrationTrusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.1.0

    knime profile image
    knime
  • Go to item
    KNIME Deep Learning - TensorFlow IntegrationTrusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.1.0

    knime profile image
    knime
  • Go to item
    KNIME Image ProcessingTrusted extension

    University of Konstanz / KNIME

    Version 1.8.1

    bioml-konstanz

Legal

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

KNIME
Open for Innovation

KNIME AG
Talacker 50
8001 Zurich, Switzerland
  • Software
  • Getting started
  • Documentation
  • Courses + Certification
  • Solutions
  • KNIME Hub
  • KNIME Forum
  • Blog
  • Events
  • Partner
  • Developers
  • KNIME Home
  • Careers
  • Contact us
Download KNIME Analytics Platform Read more about KNIME Business Hub
© 2025 KNIME AG. All rights reserved.
  • Trademarks
  • Imprint
  • Privacy
  • Terms & Conditions
  • Data Processing Agreement
  • Credits