Image Processing and Capsule Networks -

Image Processing and Capsule Networks

ICIPCN 2020
Buch | Softcover
XXII, 807 Seiten
2020 | 1st ed. 2021
Springer International Publishing (Verlag)
978-3-030-51858-5 (ISBN)
246,09 inkl. MwSt

This book emphasizes the emerging building block of image processing domain, which is known as capsule networks for performing deep image recognition and processing for next-generation imaging science. Recent years have witnessed the continuous development of technologies and methodologies related to image processing, analysis and 3D modeling which have been implemented in the field of computer and image vision. The significant development of these technologies has led to an efficient solution called capsule networks [CapsNet] to solve the intricate challenges in recognizing complex image poses, visual tasks, and object deformation. Moreover, the breakneck growth of computation complexities and computing efficiency has initiated the significant developments of the effective and sophisticated capsule network algorithms and artificial intelligence [AI] tools into existence. 

The main contribution of this book is to explain and summarize the significant state-of-the-art research advances in the areas of capsule network [CapsNet] algorithms and architectures with real-time implications in the areas of image detection, remote sensing, biomedical image analysis, computer communications, machine vision, Internet of things, and data analytics techniques. 


Efficient GAN-Based Remote Sensing Image Change Detection under Noise Conditions.- Recognition of Handwritten Digits by Image Processing Methods and Classification Models.- Convolutional Neural Network with Multi-Column Characteristics Extraction for Image Classification.- Face Detection based on Image Stitching for Class Attendance Checking.- Image Processing Technique for Effective Analysis of the Cytotoxic Activity in Human Breast Cancer Cell Lines.- Development of an algorithm for Vertebrae Identification using Speeded Up Robust Features.- Comparison of Machine Learning Algorithms for Smart License Number Plate Detection System.

 

 

 

 

 


Erscheinungsdatum
Reihe/Serie Advances in Intelligent Systems and Computing
Zusatzinfo XXII, 807 p. 457 illus., 329 illus. in color.
Verlagsort Cham
Sprache englisch
Maße 155 x 235 mm
Gewicht 1252 g
Themenwelt Informatik Grafik / Design Digitale Bildverarbeitung
Informatik Theorie / Studium Künstliche Intelligenz / Robotik
Technik
Schlagworte Artificial Neural Networks • Biomedical Engineering and Machine Learning • Capsule Networks • evolutionary computation • Genetic algorithms • ICIPCN • ICIPCN2020 • Image Processing • Neuro-fuzzy control
ISBN-10 3-030-51858-2 / 3030518582
ISBN-13 978-3-030-51858-5 / 9783030518585
Zustand Neuware
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