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====Erste Schritte====
 
====Erste Schritte====
  
- Convolutional Neural Networks
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* Convolutional Neural Networks
- Heartbeat Tutorial: [https://heartbeat.fritz.ai/analyze-and-visualize-detected-video-objects-using-keras-and-imageai-d84c99b0ae8e Analyze and Visualize Detected Video Objects Using Keras and ImageAI]
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* Heartbeat Tutorial: [https://heartbeat.fritz.ai/analyze-and-visualize-detected-video-objects-using-keras-and-imageai-d84c99b0ae8e Analyze and Visualize Detected Video Objects Using Keras and ImageAI]
  
 
====Aktueller Stand====
 
====Aktueller Stand====

Version vom 17. Mai 2019, 17:18 Uhr

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KI-SEMINAR

Projektdokumentation

Kurzbeschreibung (EN)


THE OFFICE (working title), 2019
Humans and plants live on different timescales. This is certainly one of the reasons why in everyday life, plants might often seem static and object-like to us. »The Office« (2019) makes use of existing video footage that covers large time spans, in this case, popular long-term tv shows. These productions showcase office and apartment interiors over a longer period of time, often also including houseplants which are mainly used for decorative purposes. Some of these series run over years or even decades and thus comprise many hours of footage. Convolutional neural networks are used as a tool to detect scenes involving houseplants while processing large quantities of the given video material. Selected scenes are compiled into a time-lapse movie which documents plant growth over a long period of time. While the lively movement and growth of the normally passively seeming plants becomes visible, the human activities become blurry and fade into the background.
Keywords: plants, plant-human-relationships, time, timescales, time-lapse, video, neural networks

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