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@INBOOK{Pasetto:1046796,
      author       = {Pasetto, Edoardo and Delilbasic, Amer and Riedel, Morris
                      and Cavallaro, Gabriele and Benediktsson, Jón Atli},
      title        = {{Q}uantum {C}omputing for {R}emote {S}ensing {I}mage
                      {A}nalysis},
      volume       = {09},
      address      = {n/a},
      publisher    = {WORLD SCIENTIFIC},
      reportid     = {FZJ-2025-03963},
      isbn         = {978-981-98-0714-7},
      series       = {Series in Computer Vision},
      pages        = {69 - 90},
      year         = {2025},
      comment      = {Pattern Recognition and Computer Vision in the New AI Era},
      booktitle     = {Pattern Recognition and Computer
                       Vision in the New AI Era},
      abstract     = {Quantum computing is a research field that aims at
                      developing computational models that leverage quantum
                      phenomena. The growing interest in the field of machine
                      learning as well as the recent development of available
                      quantum hardware has motivated researchers to combine the
                      two research areas, giving rise to the interdisciplinary
                      field of quantum machine learning. This chapter offers an
                      overview of the basic theoretical notions of quantum
                      computing and quantum machine learning as well as how it can
                      be applied in image processing use-cases. Specific attention
                      is given to hybrid quantum-classical models, which combine
                      the capabilities of quantum and classical computing. Some
                      example applications employing both gate-based quantum
                      computing and quantum annealing to real image processing
                      tasks within the field of remote sensing are also
                      illustrated and discussed.},
      cin          = {JSC},
      cid          = {I:(DE-Juel1)JSC-20090406},
      pnm          = {5111 - Domain-Specific Simulation $\&$ Data Life Cycle Labs
                      (SDLs) and Research Groups (POF4-511) / AIDAS - Joint
                      Virtual Laboratory for AI, Data Analytics and Scalable
                      Simulation $(aidas_20200731)$},
      pid          = {G:(DE-HGF)POF4-5111 / $G:(DE-Juel-1)aidas_20200731$},
      typ          = {PUB:(DE-HGF)7},
      doi          = {10.1142/9789819807154_0004},
      url          = {https://juser.fz-juelich.de/record/1046796},
}