KANDINSKYPatterns -- An experimental exploration environment for Pattern Analysis and Machine Intelligence

Understand

Machine intelligence is very successful at standard recognition tasks when having high-quality training data.

• There is still a significant gap between machine-level pattern recognition and human-level concept learning.
• Humans can learn under uncertainty from only a few examples and generalize these concepts to solve new problems.
• The growing interest in explainable machine intelligence, requires experimental environments and diagnostic tests to analyze weaknesses in existing approaches to drive progress in the field.