£138.05

Springer - Computational Intelligence for Image Super-Resolution

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Description

This professional volume from Springer examines the application of deep learning techniques to the complex computer vision problem of super-resolution (SR). By exploring various computational intelligence (CI) methods, the book provides a deep look into how these technologies can be used to enhance image quality and resolution. The text discusses different computer vision techniques designed to develop and improve the tools and processes essential for super-resolution tasks. Readers will gain insight into how these advanced computational methods function within practical, high-stakes environments. Designed as a valuable reference, this book covers a wide range of specialized application areas. It is particularly relevant for professionals and researchers working in biomedical engineering, healthcare, medicine, histology, and material science. Whether you are studying machine learning or applying computer vision to scientific research, this resource provides the technical foundation needed to understand modern super-resolution methodologies.

Key Features

Explores deep learning techniques specifically applied to the difficult computer vision problem of super-resolution.

Discusses various computational intelligence methods to improve image processing and resolution accuracy.

Covers diverse computer vision techniques used to develop and enhance super-resolution tools and processes.

Provides practical application insights for biomedical engineering and healthcare technology sectors.

Includes specialized research applications for medicine, histology, and material science fields.

Serves as a comprehensive technical reference for experts in AI and machine learning.

Product Specifications

Format
hardcover
Domain
Amazon UK
Release Date
29 May 2021
Listed Since
15 December 2020

Barcode

No barcode data available

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