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Herausgeber: 
  • Aditi Sharma
  • Prasanalakshmi Balaji
  • K. Martin Sagayam
  • Metaheuristic Algorithms and Optimizing Neural Networks for Biomedical Image Processing 
     

    (Buch)
    Dieser Artikel gilt, aufgrund seiner Grösse, beim Versand als 3 Artikel!


    Übersicht

    Auf mobile öffnen
     
    Lieferstatus:   i.d.R. innert 7-14 Tagen versandfertig
    Veröffentlichung:  August 2025  
    Genre:  Naturwissensch., Medizin, Technik 
     
    Biomedicine / Burnout Detection / Deep Learning / Disease Detection / genetics / Image processing / Internet of things / Medical imaging
    ISBN:  9798337305240 
    EAN-Code: 
    9798337305240 
    Verlag:  IGI Global 
    Einband:  Kartoniert  
    Sprache:  English  
    Dimensionen:  H 254 mm / B 178 mm / D 29 mm 
    Gewicht:  1000 gr 
    Seiten:  538 
    Bewertung: Titel bewerten / Meinung schreiben
    Inhalt:
    Metaheuristic algorithms emerge as powerful tools for optimizing complex systems, particularly in neural networks, where traditional methods may cause challenges. In biomedical image processing, the integration of metaheuristics like genetic algorithms, particle swarm optimization, and differential evolution offers promising improvements in neural network performance. These algorithms help improve hyperparameters and optimize architectures, enhancing the accuracy of tasks like disease detection, image segmentation, and classification. Further research into this convergence between metaheuristic optimization and deep learning may help advance medical diagnostics and healthcare technologies. Metaheuristic Algorithms and Optimizing Neural Networks for Biomedical Image Processing explores the optimization of neural networks for biomedical image analysis. It provides valuable insights into advanced image processing for improved healthcare, advanced technology, and potential scientific and computational breakthroughs. This book covers topics such as medical imaging, genetics, and psychology, and is a useful resource for business owners, computer engineers, medical professionals, academicians, researchers, and data scientists.

      



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