Concept Extraction

ECLAD: Extracting Concepts with Local Aggregated Descriptors
A novel method for automatic concept extraction and localization based on representations obtained through pixel-wise aggregations of CNN activation maps.
Andres Felipe Posada-Moreno, Nikita Surya, Sebastian Trimpe
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Scalable Concept Extraction in Industry 4.0
Applying concept extraction (ECLAD) for explaining CNNs in industrial use cases.
Andres Felipe Posada-Moreno, Kai Müller, Florian Brillowski, Friedrich Solowjow, Thomas Gries, Sebastian Trimpe
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Explaining Neural Networks Through Concept Extraction
This research project focuses on the methodological and application aspects of how to explain what a deep neural network learns through training. Specifically, this project tackles the development of methods for concept extraction, localization, and learning, as well as their applications in industrial scenarios.
Explaining Neural Networks Through Concept Extraction