KC Santosh – författare

Winner of the "Outstanding Academic Title" recognition by Choice for the 2020 OAT Awards.

The Choice OAT Award represents the highest caliber of scholarly titles that have been reviewed by Choice and conveys the extraordinary recognition of the academic community.

The book discusses varied topics pertaining to advanced or up-to-date techniques in medical imaging using artificial intelligence (AI), image recognition (IR) and machine learning (ML) algorithms/techniques. Further, coverage includes analysis of chest radiographs (chest x-rays) via stacked generalization models, TB type detection using slice separation approach, brain tumor image segmentation via deep learning, mammogram mass separation, epileptic seizures, breast ultrasound images, knee joint x-ray images, bone fracture detection and labeling, and diabetic retinopathy. It also reviews 3D imaging in biomedical applications and pathological medical imaging.

Winner of the "Outstanding Academic Title" recognition by Choice for the 2020 OAT Awards.

The Choice OAT Award represents the highest caliber of scholarly titles that have been reviewed by Choice and conveys the extraordinary recognition of the academic community.

The book discusses varied topics pertaining to advanced or up-to-date techniques in medical imaging using artificial intelligence (AI), image recognition (IR) and machine learning (ML) algorithms/techniques. Further, coverage includes analysis of chest radiographs (chest x-rays) via stacked generalization models, TB type detection using slice separation approach, brain tumor image segmentation via deep learning, mammogram mass separation, epileptic seizures, breast ultrasound images, knee joint x-ray images, bone fracture detection and labeling, and diabetic retinopathy. It also reviews 3D imaging in biomedical applications and pathological medical imaging.

Document Processing Using Machine Learning aims at presenting a handful of resources for students and researchers working in the document image analysis (DIA) domain using machine learning since it covers multiple document processing problems. Starting with an explanation of how Artificial Intelligence (AI) plays an important role in this domain, the book further discusses how different machine learning algorithms can be applied for classification/recognition and clustering problems regardless the type of input data: images or text.

In brief, the book offers comprehensive coverage of the most essential topics, including:

· The role of AI for document image analysis

· Optical character recognition

· Machine learning algorithms for document analysis

· Extreme learning machines and their applications

· Mathematical foundation for Web text document analysis

· Social media data analysis

· Modalities for document dataset generation

This book serves both undergraduate and graduate scholars in Computer Science/Information Technology/Electrical and Computer Engineering. Further, it is a great fit for early career research scientists and industrialists in the domain.

Document Processing Using Machine Learning aims at presenting a handful of resources for students and researchers working in the document image analysis (DIA) domain using machine learning since it covers multiple document processing problems. Starting with an explanation of how Artificial Intelligence (AI) plays an important role in this domain, the book further discusses how different machine learning algorithms can be applied for classification/recognition and clustering problems regardless the type of input data: images or text.

In brief, the book offers comprehensive coverage of the most essential topics, including:

· The role of AI for document image analysis

· Optical character recognition

· Machine learning algorithms for document analysis

· Extreme learning machines and their applications

· Mathematical foundation for Web text document analysis

· Social media data analysis

· Modalities for document dataset generation

This book serves both undergraduate and graduate scholars in Computer Science/Information Technology/Electrical and Computer Engineering. Further, it is a great fit for early career research scientists and industrialists in the domain.

The 19 full papers and 14 short papers presented were carefully reviewed and selected from 84 submissions. The papers are organized in the following topical sections:​ healthcare: medical imaging and informatics; computer vision and pattern recognition; document analysis and recognition; signal processing and machine learning; satellite imaging and remote sensing. 

This book presents the proceedings of the 3rd International Conference on Artificial Intelligence and Computer Vision (AICV’2023) which will be held in Marrakesh, Morocco, during March 05–07, 2023. This international conference, which highlighted essential research and developments in the fields of artificial intelligence and computer visions, was organized by the computer, Networks, Mobility and Modeling Laboratory (IR2M), Faculty of Sciences and Techniques, Hassan First University, Settat, Morocco, the Scientific Research Group in Egypt (SRGE), Cairo University, and the Automated Systems & Soft Computing Lab (ASSCL), Prince Sultan University, Riyadh, Saudi Arabia. The book is divided into sections, covering the following topics: swarm-based optimization mining and data analysis, deep learning and applications, machine learning and applications, image processing and computer vision, sentiment analysis, and recommendation systems, and software-defined network and telecommunication.

The two-volume proceedings set CCIS 2430-2431 constitutes the revised selected papers of the 6th International Conference on Soft Computing and its Engineering Applications, icSoftComp 2024, held in Bangkok, Thailand, during December 10–12, 2024.

The 58 full papers and 3 short papers included in this book were carefully reviewed and selected from 501 submissions. They were organized in topical sections as follows: Part I : Theory and Methods.Part II : Theory and Methods; Systems and Applications; Hybrid Techniques; Soft Computing for Smart World.

The two-volume proceedings set CCIS 2430-2431 constitutes the revised selected papers of the 6th International Conference on Soft Computing and its Engineering Applications, icSoftComp 2024, held in Bangkok, Thailand, during December 10–12, 2024.

The 58 full papers and 3 short papers included in this book were carefully reviewed and selected from 501 submissions. They were organized in topical sections as follows: Part I: Theory and Methods.Part II: Theory and Methods; Systems and Applications; Hybrid Techniques; Soft Computing for Smart World.