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 [Caps Net] 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 [Caps Net] 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.
Inhaltsverzeichnis
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.
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