Second International Conference on Image Processing and Capsule Networks (eBook, PDF)

ICIPCN 2021
Redaktion: Chen, Joy Iong-Zong; Du, Ke-Lin; Iliyasu, Abdullah M.; Tavares, João Manuel R. S.

• Format: PDF

Produktbeschreibung

This book includes the papers presented in 2nd International Conference on Image Processing and Capsule Networks [ICIPCN 2021]. In this digital era, image processing plays a significant role in wide range of real-time applications like sensing, automation, health care, industries etc. Today, with many technological advances, many state-of-the-art techniques are integrated with image processing domain to enhance its adaptiveness, reliability, accuracy and efficiency. With the advent of intelligent technologies like machine learning especially deep learning, the imaging system can make decisions more and more accurately. Moreover, the application of deep learning will also help to identify the hidden information in volumetric images. Nevertheless, capsule network, a type of deep neural network, is revolutionizing the image processing domain; it is still in a research and development phase. In this perspective, this book includes the state-of-the-art research works that integrate intelligent techniques with image processing models, and also, it reports the recent advancements in image processing techniques. Also, this book includes the novel tools and techniques for deploying real-time image processing applications.

The chapters will briefly discuss about the intelligent image processing technologies, which leverage an authoritative and detailed representation by delivering an enhanced image and video recognition and adaptive processing mechanisms, which may clearly define the image and the family of image processing techniques and applications that are closely related to the humanistic way of thinking.

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Produktdetails

• Verlag: Springer Nature Switzerland
• Seitenzahl: 825
• Erscheinungstermin: 9. September 2021
• Englisch
• ISBN-13: 9783030847609
• Artikelnr.: 62560765

Inhaltsangabe

A Survey of Machine Learning Techniques Applied for Automatic Traffic Light Recognition.- Machine Learning based Detection and Classification of Heart Abnormalities.- An Evaluation of Multiclass Leaf Classification using Transfer Learning Techniques.- Scene Generated with Text guidance(VAAB System).- Machine Learning Approaches for Image Quality Improvement.- Natural Disaster Prediction by using Image based Deep Learning and Machine Learning.- A Novel Multi-Objective Differential Evolution Algorithm for Clustering Data Streams.- An Algorithm for Pre-processing of Areca nut for Quality Classification.- An Effect of Binarization on Handwritten Digits Recognition by Hierarchical Neural Networks.- Deep Convolutional Neural Networks (CNNs) to Detect Abnormality in Musculoskeletal Radiographs.