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  • Sách/Book

  • Artificial Intelligence in a Throughput Model : Some Major Algorithms

    • Authors: Waymond Rodgers (2020)

  • This book provides an overview of the existing biometric technologies, decision-making algorithms and the growth opportunity in biometrics. The book proposes a throughput model, which draws on computer science, economics and psychology to model perceptual, informational sources, judgmental processes and decision choice algorithms
  • Sách/Book

  • Hands-On Gradient Boosting with XGBoost and scikit-learn

    • Authors: Corey Wade (2020)

  • The book introduces machine learning and XGBoost in scikit-learn before building up to the theory behind gradient boosting. You'll cover decision trees and analyze bagging in the machine learning context, learning hyperparameters that extend to XGBoost along the way. You'll build gradient boosting models from scratch and extend gradient boosting to big data while recognizing speed limitations using timers.
  • Sách/Book

  • Artificial Intelligence and Robotics

    • Authors: Huimin Lu (2021)

  • This book provides insights into research in the field of artificial intelligence in combination with robotics technologies. The integration of artificial intelligence and robotic technologies is a highly topical area for researchers and developers from academia and industry around the globe, and it is likely that artificial intelligence will become the main approach for the next generation of robotics research.
  • Sách/Book

  • Elastic Optical Networks : Fundamentals, Design, Control, and Management

    • Authors: Bijoy Chand Chatterjee (2020)

  • The book explains the fragmentation problem in EONs, discusses, and analyzes the major conventional spectrum allocation policies in terms of the fragmentation effect in a network. The taxonomies of the fragmentation management approaches are presented along with different node architectures. State-of-the-art fragmentation management approaches are looked at.
  • Sách/Book

  • Artificial Intelligence and Deep Learning in Pathology

    • Authors: Stanley Cohen (2021)

  • Focuses heavily on applications in medicine, especially pathology, making unfamiliar material accessible and avoiding complex mathematics whenever possible. Covers digital pathology as a platform for primary diagnosis and augmentation via deep learning, whole slide imaging for 2D and 3D analysis, and general principles of image analysis and deep learning.
  • Sách/Book

  • Artificial Intelligence Techniques for Satellite Image Analysis

    • Authors: D. Jude Hemanth (2021)

  • The main objective of this book is to provide a common platform for diverse concepts in satellite image processing. In particular it presents the state-of-the-art in Artificial Intelligence (AI) methodologies and shares findings that can be translated into real-time applications to benefit humankind