Intelligent Computing and Analytics in Image Processing
Will be published approx. on 4. August 2026
310 pages
E-Book
978-1-040-90335-3 (ISBN)
Description
This volume explores a wide range of advanced applications of intelligent technologies in image processing across diverse domains. It examines biological and biomedical imaging, highlighting the use of machine learning and deep learning techniques for the diagnosis and detection of conditions such as brain tumors, diabetes, pneumonia, and heart disease. Beyond healthcare, the book presents applications of intelligent computing in areas including plant identification and leaf disease detection, fruit classification and counting, forensic analysis, facial detection and emotion recognition, and sketch-tophoto synthesis. It also provides insights into key deep learning approaches, such as convolutional neural networks (CNNs) and the Inception V3 architecture, along with image enhancement techniques like contrast limited adaptive histogram equalization (CLAHE).
More details
Language
English
Place of publication
United Kingdom
Publishing group
Taylor & Francis Ltd
Target group
College/higher education
Professional and scholarly
Illustrations
5 Line drawings, color; 81 Line drawings, black and white; 1 Halftones, color; 38 Halftones, black and white; 130 Illustrations, black and white
ISBN-13
978-1-040-90335-3 (9781040903353)
Copyright in bibliographic data is held by Nielsen Book Services Limited or its licensors: all rights reserved.
Schweitzer Classification
Other editions
Additional editions
Samarjeet Borah | Jambi Ratna Raja Kumar | Laxmi Bewoor
Intelligent Computing and Analytics in Image Processing
Book
approx. 08/2026
1st Edition
Apple Academic Press Inc.
€185.50
Not yet published
Persons
Samarjeet Borah, PhD, is Professor and Head of the Department of Computer Applications at SMIT, Sikkim Manipal University, India. He has led funded research projects, published research papers in peer reviewed journals and conference proceedings, and organized numerous national and international workshops and conferences. He has contributed to several book volumes and journals published by leading publishers and serves as Editor-in-Chief of the book series Research Notes on Computing and Communication Sciences.
Jambi Ratna Raja Kumar, PhD, is the Principal of Genba Sopanrao Moze College of Engineering, Pune, Maharashtra, India. With over 17 years of teaching and research experience, he has published research papers and has seven patents on artificial intelligence and machine learning. He has guided many undergraduate, postgraduate, and PhD students and has received several awards, including being named Distinguished Principal at the Dr. APJ Abdul Kalam Puraskar 2022 and Best Innovative Leader of the Year (Maharashtra) at the Asia Education Summit and Awards 2019.
Laxmi Bewoor, PhD, is an Associate Professor of Computer Engineering at the Vishwakarma Institute of Information Technology, India. She holds six international patents, has published articles in journals and conferences, and is a reviewer for leading journals. Dr. Bewoor is also a resource person for several academic institutes. She has chaired sessions at international conferences and collaborated with many industries and research organizations.
Rahul Raghvendra Joshi, PhD, is an Associate Professor at the Symbiosis Institute of Technology, Pune, India. He has more than 17 years of experience and over 100 publications to his name. He is a reviewer for reputed Scopus-indexed journals. His research areas include computational intelligence, multicriteria decision-making, blockchain, and cloud computing.
Mahendra Prabhakar Deore, PhD, is an Assistant Professor of Computer Engineering at MKSSS's Cummins College of Engineering for Women, Pune, India. With over 16 years of dedicated teaching experience at the undergraduate level, he possesses deep knowledge and expertise in this domain. Throughout his academic journey, Dr. Deore has authored and published more than 20 SCI- and Scopusindexed research papers.
Jambi Ratna Raja Kumar, PhD, is the Principal of Genba Sopanrao Moze College of Engineering, Pune, Maharashtra, India. With over 17 years of teaching and research experience, he has published research papers and has seven patents on artificial intelligence and machine learning. He has guided many undergraduate, postgraduate, and PhD students and has received several awards, including being named Distinguished Principal at the Dr. APJ Abdul Kalam Puraskar 2022 and Best Innovative Leader of the Year (Maharashtra) at the Asia Education Summit and Awards 2019.
Laxmi Bewoor, PhD, is an Associate Professor of Computer Engineering at the Vishwakarma Institute of Information Technology, India. She holds six international patents, has published articles in journals and conferences, and is a reviewer for leading journals. Dr. Bewoor is also a resource person for several academic institutes. She has chaired sessions at international conferences and collaborated with many industries and research organizations.
Rahul Raghvendra Joshi, PhD, is an Associate Professor at the Symbiosis Institute of Technology, Pune, India. He has more than 17 years of experience and over 100 publications to his name. He is a reviewer for reputed Scopus-indexed journals. His research areas include computational intelligence, multicriteria decision-making, blockchain, and cloud computing.
Mahendra Prabhakar Deore, PhD, is an Assistant Professor of Computer Engineering at MKSSS's Cummins College of Engineering for Women, Pune, India. With over 16 years of dedicated teaching experience at the undergraduate level, he possesses deep knowledge and expertise in this domain. Throughout his academic journey, Dr. Deore has authored and published more than 20 SCI- and Scopusindexed research papers.
Content
Preface Introduction 1. Deep Learning-Based Classification of Brain Tumor MRI Images for Cyber-Physical Machines with ResNet-50 and Image Augmentation 2. Identification of Non-Proliferative Diabetic Retinopathy Stages Using the CLAHE of Data Preprocessing 3. Optimized Deep Learning Model for Predicting Brain Tumors 4. Heart Disease Prediction Using Machine Learning 5. Deep Learning-Based Pneumonia Detection System Using VGG16 and Inception V3 for NIH Chest X-Ray Images 6. Comparative Study Using Deep Learning for Detecting Plant Type and Leaf Disease 7. Performance Analysis of Various Machine Learning Techniques for Fruit Classification and Counting from Images 8. An Analysis on Image Edge-Detection Techniques for Forensics Analysis 9. Enabling Communication Strategies: Indian Alpha-Sign Gesture Recognition 10. Evaluating Face Detection for Real-Time Emotion Recognition 11. Deep Learning-Based Song Recommendation System Using Facial Expression 12. Sketch-to-Photo Synthesis Using the Autoencoder-Kalman Filter 13. Comparative Review of Image Filtering in Spatial and Frequency Domain 14. An Analysis on Feature Descriptors Used in Computer Vision 15. Monitoring of Human Poses for Tracking Gym Activities 16. Enhancing Heart Failure Survivability Prediction: A Machine Learning Approach Using SMOTE and a Decorate Ensemble of a C4.5 Decision Tree 17. Utilizing Adaptive Feature Scaling and Dynamic Contextual Graph Networks to Improve Captioning of Images through the Recognition of Unseen Relationships Index
