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Intelligent algorithms : theory and practice /

In this book, the latest achievements of the computation time analysis theory and practical applications of intelligent algorithms are set out. There are five chapters: (1) new method of intelligent algorithm computation time analysis; (2)Application of intelligent algorithms in computer vision; (3)...

詳細記述

保存先:
書誌詳細
主要な著者: Huang, Han (著者), Hao, Zhifeng (著者)
フォーマット: 電子媒体 eBook
言語:英語
出版事項: Amsterdam, Netherlands ; London, United Kingdom ; Cambridge, MA, United States : Elsevier, [2024]
主題:
Computer algorithms.
Artificial intelligence.
Algorithmes.
Intelligence artificielle.
algorithms.
artificial intelligence.
Artificial intelligence
Computer algorithms
Electronic books.
オンライン･アクセス:ScienceDirect
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目次:
  • Front Cover
  • Intelligent Algorithms
  • Copyright Page
  • Contents
  • About the authors
  • Preface
  • Introduction
  • 1 Application of intelligent algorithms in the field of computer vision
  • 1.1 Precise capture of translucent visual effects: sampling algorithm based on pixel-level multiobjective optimization
  • 1.1.1 Overview of Research Progress
  • 1.1.2 Scientific principles
  • 1.1.2.1 Problem description
  • 1.1.2.2 A multiobjective image matting algorithm based on pixel-level global sampling
  • 1.1.2.2.1 Pixel-level discrete multiobjective sampling strategy
  • 1.1.2.2.2 Fast discrete multiobjective optimization algorithm
  • 1.1.2.3 Experimental results and discussion
  • 1.1.2.3.1 Performance verification experiment of the pixel-level multiobjective global sampling algorithm
  • 1.1.2.3.2 Performance verification experiment of the pixel-level multiobjective global sampling-based matting algorithm
  • 1.1.3 Summary
  • 1.2 Strong collaboration of fuzzy logic and evolutionary computing
  • 1.2.1 Overview of research progress
  • 1.2.2 Scientific principles
  • 1.2.2.1 Problem description
  • 1.2.2.2 Multiobjective collaborative optimization image matting algorithm based on fuzzy multicriteria evaluation and decom...
  • 1.2.2.2.1 Fuzzy multicriteria pixel pair evaluation method
  • 1.2.2.2.2 Multiobjective collaborative optimization algorithm based on decomposition
  • 1.2.2.3 Experimental results and discussion
  • 1.2.2.3.1 Multiobjective optimization algorithm selection experiment
  • 1.2.2.3.2 Fuzzy multicriteria pixel pair evaluation accuracy experiment
  • 1.2.2.3.3 Comparative experiment on optimization performance of multiobjective collaborative optimization algorithm based o...
  • 1.2.2.3.4 Multiobjective collaborative optimization method for image matting based on fuzzy multicriteria evaluation and de...
  • 1.2.3 Summary
  • 1.3 Another masterpiece when medicine meets artificial intelligence
  • 1.3.1 Overview of research progress
  • 1.3.2 Scientific principles
  • 1.3.2.1 Blood vessel segmentation algorithm based on hierarchical matting model
  • 1.3.2.1.1 Image segmentation
  • 1.3.2.1.2 Extraction of vascular skeleton
  • 1.3.2.1.3 Hierarchical matting model
  • 1.3.2.1.4 Stratifying the unknown pixels
  • 1.3.2.1.5 Correlation function
  • 1.3.2.1.6 Hierarchical update
  • 1.3.2.2 Experimental analysis
  • 1.3.3 Summary
  • 1.4 "Deep learning+image matting enhancement" trial with great effectiveness: pedestrian classification in infrared images
  • 1.4.1 Overview of research progress
  • 1.4.2 Scientific principles
  • 1.4.2.1 Pedestrian classification algorithm based on automatic image matting and enhancement for infrared images
  • 1.4.2.2 Preprocessing algorithm for infrared pedestrian images based on automatic image matting
  • 1.4.2.2.1 Automatic algorithm for generating pedestrian trimap in infrared images
  • 1.4.2.2.2 Far-infrared pedestrian extraction

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