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Semantic Segmentation using Deep Learning

Om Semantic Segmentation using Deep Learning

This research addresses multifaceted environmental challenges linked to urbanization by introducing a transferable UNET model designed for precise greenery detection in high-resolution satellite imagery. The dataset, consisting of 72 images captured over Dubai by MBRSC satellites and annotated by the Roia Foundation, serves as the foundation of our study. While rooted in Dubai, the model's adaptability extends beyond regional confines, offering a versatile solution to a spectrum of global urban environmental challenges. In addition to accurate greenery detection, the UNET model provides a holistic approach to urban land cover classification.

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  • Språk:
  • Engelsk
  • ISBN:
  • 9786207466214
  • Bindende:
  • Paperback
  • Utgitt:
  • 19. februar 2024
  • Dimensjoner:
  • 152x229x4 mm.
  • Vekt:
  • 100 g.
  Gratis frakt
Leveringstid: 2-4 uker
Forventet levering: 17. januar 2025
Utvidet returrett til 31. januar 2025
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Beskrivelse av Semantic Segmentation using Deep Learning

This research addresses multifaceted environmental challenges linked to urbanization by introducing a transferable UNET model designed for precise greenery detection in high-resolution satellite imagery. The dataset, consisting of 72 images captured over Dubai by MBRSC satellites and annotated by the Roia Foundation, serves as the foundation of our study. While rooted in Dubai, the model's adaptability extends beyond regional confines, offering a versatile solution to a spectrum of global urban environmental challenges. In addition to accurate greenery detection, the UNET model provides a holistic approach to urban land cover classification.

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