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Current version: 5.0 (21-Sep-2016)

Release highlights:

  • Deep Learning for image classification
    • Train convolutional networks with one command
    • Get direct feedback when designing network architecture
    • GUI with training progress
  • Improvements of image feature extraction
  • Upgrade of Support Vector Machine
Detailed release notes

Get answers

Get inspired

  • Train deep nets on your images.
    Deep Learning Tutorial
  • Outlier removal built in a classifier.
    Classifier removing outliers
  • Execution of real-time classifiers outside Matlab
    Out-of-Matlab execution
  • Object detection
    Object detection
  • Quick image labeling
    Quick image labeling
  • Interactive scatter
    Interactive scatter
  • Local image features
    Local image features
  • Detectors explained
    Detectors explained
  • Find rare samples
    Find rare samples
  • Labels by clustering
    Labels by clustering
  • Cross-validation example
    Cross-validation example
  • Classifier tuning
    Classifier tuning
  • Texture classification
    Texture classification
  • Why to use meta-data?
    Why to use meta-data?
  • Hand-drawn classifiers
    Hand-drawn classifiers
  • Feature distributions
    Feature distributions
  • Training on multiple images
    Training on multiple images
  • Run classifiers in Excel
    Run classifiers in Excel

Get informed

Latest newsletter:

Newsletter December 2016

metal sorting robot using hyperspectral imaging and perClass
  • Exhibitions: Visit us at AgriFoodTech on 14-15 December
  • Announcement: Machine Learning course: 20-24 March 2017
  • Customer story: Metal sorting using Hyperspectral imaging
  • From the blog: Impression from the Vision fair in Stuttgart
  • From the blog: Autumn perClass course was fully booked again

See all newsletters