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Entropy in Image Analysis III

Entropy in Image Analysis III

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Image analysis can be applied to rich and assorted scenarios; therefore, the aim of this recent research field is not only to mimic the human vision system. Image analysis is the main methods that computers are using today, and there is body of knowledge that they will be able to manage in a totally unsupervised manner in future, thanks to their artificial intelligence. The articles published in the book clearly show such a future.

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Keywords

  • anode heel effect
  • bat optimization
  • cellular neural network
  • Chaos
  • circular-step wedge
  • color image encryption
  • Computed Tomography
  • Computer-assisted diagnosis
  • continuous-time image reconstruction
  • contrast-detail
  • cryptanalysis
  • Diffusion
  • Entropy
  • fwi
  • gamma correction
  • Hilbert curve
  • History of engineering & technology
  • HSV color space
  • human crowd behavior (HCB)
  • hyper-chaotic
  • hyperchaotic
  • image and video compression
  • image encryption
  • image encryption/decryption
  • image enhancement
  • image segmentation
  • improved entropy (IE)
  • inverse problems
  • iterative reconstruction
  • Jaccard similarity
  • low-light image
  • Machine learning
  • maximum-likelihood expectation-maximization method
  • multi-person counting
  • multiple bit operation
  • mutual information
  • n/a
  • Newton-Raphson’s method
  • particles gradient motion (PGM)
  • permutation
  • power-divergence measure
  • prior information
  • regularization
  • Retinex
  • ribonucleic acid
  • run-length-based entropy coding
  • scan route
  • secure communication
  • security analysis
  • speeded up robust features (SURF)
  • spleen injury detection
  • Technology, engineering, agriculture
  • Technology: general issues
  • transformed Zigzag
  • visible ratio

Links

DOI: 10.3390/books978-3-0365-3516-6

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