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Aesthetics in Digital Photography

Om Aesthetics in Digital Photography

Automatically evaluating the aesthetic qualities of a photograph is a current challenge for artificial intelligence technologies, yet it is also an opportunity to open up new economic and social possibilities. Aesthetics in Digital Photography presents theories developed over the last 25 centuries by philosophers and art critics, who have sometimes been governed by the objectivity of perception, and other times, of course, by the subjectivity of human judgement. It explores the advances that have been made in neuro-aesthetics and their current limitations. In the field of photography, this book puts aesthetic hypotheses up against experimental verification, and then critically examines attempts to "scientifically" measure this beauty. Special attention is paid to artificial intelligence techniques, taking advantage of machine learning methods and large databases.

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  • Språk:
  • Engelsk
  • ISBN:
  • 9781786307538
  • Bindende:
  • Hardback
  • Sider:
  • 336
  • Utgitt:
  • 15. august 2023
  • Dimensjoner:
  • 161x22x240 mm.
  • Vekt:
  • 651 g.
  Gratis frakt
Leveringstid: 2-4 uker
Forventet levering: 19. mai 2025

Beskrivelse av Aesthetics in Digital Photography

Automatically evaluating the aesthetic qualities of a photograph is a current challenge for artificial intelligence technologies, yet it is also an opportunity to open up new economic and social possibilities. Aesthetics in Digital Photography presents theories developed over the last 25 centuries by philosophers and art critics, who have sometimes been governed by the objectivity of perception, and other times, of course, by the subjectivity of human judgement. It explores the advances that have been made in neuro-aesthetics and their current limitations. In the field of photography, this book puts aesthetic hypotheses up against experimental verification, and then critically examines attempts to "scientifically" measure this beauty. Special attention is paid to artificial intelligence techniques, taking advantage of machine learning methods and large databases.

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