The term "visualisation of neural networks" is primarily used in the fields of artificial intelligence and big data. Neural networks are complex systems that enable machines to learn - for example, when recognising faces in photos or translating languages. Because these networks often have millions of connections and parameters, it is difficult for humans to understand exactly how they work.
The visualisation of neural networks refers to the representation of these complex processes in clear images or diagrams. This makes it possible to understand how the machine arrives at a decision. For developers and decision-makers, this makes it clear where the network works particularly well or badly.
A typical example: In a neural network that detects tumours on X-ray images, the visualisation shows in colour which areas of the image the network is paying particular attention to. Doctors can immediately see whether the system is correctly recognising important features. The visualisation of neural networks therefore helps to create trust in artificial intelligence and make its results more comprehensible.
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