Publisher 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).

Table of Contents

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

Details