Computer Science › Section L · Artificial intelligence › Topic L.2
Perception: vision and language
Before an agent can act sensibly it has to make sense of what it sees and hears. This topic follows how machines recognise symbols and scenes in images and how they untangle the meaning of sentences, from early hand-built methods to the learned systems that now dominate.
In this topic
- Perceiving is more than recording
- Worked example: matching a digit to templates
- Matching features instead
- From pixels to meaning
- Worked example: finding edges in a row of pixels
- Why natural language is hard
- Three levels of analysis
- Worked example: 'I saw her duck'
- Working with whole documents
- Learning to perceive
- Common mistakes to avoid
- Key takeaways
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