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  • Sách/Book

  • Deep network design for medical image computing : principles and applications

    • Authors: Liao, Haofu (2022)

  • Deep Network Design for Medical Image Computing: Principles and Applications covers a range of MIC tasks and discusses design principles of these tasks for deep learning approaches in medicine. These include skin disease classification, vertebrae identification and localization, cardiac ultrasound image segmentation, 2D/3D medical image registration for intervention, metal artifact reduction, sparse-view artifact reduction, etc.
  • Sách/Book

  • Network Tomography: Identifiability, Measurement Design, and Network State Inference

    • Authors: He, Ting (2021)

  • It describes the main types of mathematical problems, along with their solutions and properties, and emphasizes the actions that can be taken to improve the accuracy of network tomography. With proofs and derivations introduced in an accessible language for easy understanding, this is an essential resource for professional engineers, academic researchers, and graduate students in network management and network science.