SECAI Core · phase 2 of 15
Convolutional neural network
A deep learning method designed to process and analyze visual data by mimicking the way the human brain processes images; especially effective for tasks involving image recognition, object detection, and other image processing analyses.
The Explain card
- Plain English
- A convolutional neural network (CNN) is a deep learning design for images. It scans small patches, a bit like the visual cortex, to spot edges, shapes and finally whole objects.
- Example
- A CNN in a building's camera system identifies faces and licence plates. A researcher prints a patterned sticker on a cap and the camera no longer recognises a face at all.
- Why it matters
- CNNs are sensitive to pixel-level tweaks humans cannot see, which makes adversarial patches and perturbations effective against recognition systems used for access control and safety.
- Hook
- It sees the world in patches, so a patch can blind it.
Where it sits in the deck
Phase 2: How Models Are Built: Architectures and Learning Mechanics
With the paradigms named, zoom in on the architectural building blocks that turn data into trained artifacts.
