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09_​Simple_​Anomaly_​Detection_​Using_​A_​Convolutional_​Net

Simple Anomaly Detection Using a Convolutional Network

This workflow shows how to do anomaly detection of the MNIST dataset using a convolutional network.

Workflow Requirements
KNIME Analytics Platform 3.2.0
KNIME Deeplearning4J Integration
KNIME Deeplearning4J Integration Image Processing Extension

Simple Anomaly Detection Using a Convolutional NetworkThis workflow shows how to do anomaly detection of the MNIST dataset using aconvolutional network. Sort by errorSelect the 10 exampleswith highes errorView high error examples Calculate Error Create andTrain Network Sorter Row Sampling Image Viewer Read Images Simple Anomaly Detection Using a Convolutional NetworkThis workflow shows how to do anomaly detection of the MNIST dataset using aconvolutional network. Sort by errorSelect the 10 exampleswith highes errorView high error examplesCalculate Error Create andTrain Network Sorter Row Sampling Image Viewer Read Images

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To use this workflow in KNIME, download it from the below URL and open it in KNIME:

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Created by: David Kolb
Created at: 2016-05-18
On NodePit since: 2019-07-12
Last update: 2026-07-12
Created with KNIME version: v4.1.0
Tags: deeplearningmachine learninganomaly detectionneural networksconvolutional

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