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Image Processing and Capsule Networks : ICIPCN 2020 ; Bangkok, Thailand, 20-21 May, 2021 / edited by Joy Long-Zong Chen, João Manuel R. S. Tavares, Subarna Shakya, Abdullah M. Iliyasu.
Format
Book
Language
English
Εdition
1st edition.
Published/Created
Cham : Springer International Publishing : Imprint: Springer, 2021.
Description
1 online resource (827 pages)
Availability
Available Online
Springer Nature - Springer Intelligent Technologies and Robotics eBooks 2021 English International
Details
Subject(s)
Computational intelligence
[Browse]
Optical data processing
[Browse]
Editor
Chen, Joy Long-Zong
[Browse]
Tavares, João Manuel R. S.
[Browse]
Shakya, Subarna
[Browse]
Iliyasu, Abdullah M.
[Browse]
Series
Advances in Intelligent Systems and Computing, 1200
[More in this series]
Advances in Intelligent Systems and Computing, 2194-5357 ; 1200
[More in this series]
Summary note
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. .
Contents
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. .
Show 4 more Contents items
ISBN
3-030-51859-0
Doi
10.1007/978-3-030-51859-2
Statement on language in description
Princeton University Library aims to describe library materials in a manner that is respectful to the individuals and communities who create, use, and are represented in the collections we manage.
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