Metaheuristic Algorithms and Optimizing Neural Networks for Biomedical Image Processing (Hardcover)

Prasanalakshmi Balaji

ISBN 13: 9798337305233

Published by IGI Global, Hershey, 2025

About this Item

Hardcover. 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. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.

Seller Inventory # 9798337305233

Bibliographic Details

• Title: Metaheuristic Algorithms and Optimizing Neural Networks for Biomedical Image Processing (Hardcover)
• Publisher: IGI Global, Hershey
• Publication Date: 2025
• Language: English
• ISBN 13: 9798337305233
• Binding: Hardcover
• Condition: new

About this title

Synopsis

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.