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| en:safeav:maps:ai [2025/10/21 16:18] – [Data Requirements] kosnark | en:safeav:maps:ai [2026/04/24 09:43] (current) – raivo.sell |
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| ====== AI-based Perception and Scene Understanding ====== | ====== AI-based Perception and Scene Understanding ====== |
| {{:en:iot-open:czapka_b.png?50| Bachelors (1st level) classification icon }} | |
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| <todo @bertlluk #bertlluk:2025-06-25></todo> | |
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| Advances in AI, especially the convolutional neural network, allow us to process raw sensory information and recognize objects and categorize them into classes with higher levels of abstraction (pedestrians, cars, trees, etc.). Taking these categories into account allows autonomous vehicles to understand the scene and reason about future actions of the vehicle as well as about the other participants in road traffic and make assumptions on/predictions of their possible interactions. This section elaborates on the comparison of commonly used methods, their advantages, and weaknesses. | Advances in AI, especially the convolutional neural network, allow us to process raw sensory information and recognize objects and categorize them into classes with higher levels of abstraction (pedestrians, cars, trees, etc.). Taking these categories into account allows autonomous vehicles to understand the scene and reason about future actions of the vehicle as well as about the other participants in road traffic and make assumptions on/predictions of their possible interactions. This section elaborates on the comparison of commonly used methods, their advantages, and weaknesses. |
