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Full Description
As computers and intelligent machines evolve at an unprecedented pace, the quest to replicate human intelligence in software and systems has become a defining challenge of our time. Research Advances in Intelligent Computing: Volume 3 explores this dynamic field, where artificial intelligence (AI) and computational models converge to create systems capable of learning, reasoning, and problem-solving. Drawing inspiration from human cognition, intelligent computing (IC) integrates AI techniques such as machine learning, neural networks, deep learning, evolutionary algorithms, and swarm intelligence to build adaptive, efficient, and autonomous systems. These technologies are now at the heart of innovations across disciplines - from robotics and natural language processing to agriculture, medicine, and economics. This book presents a comprehensive view of the latest advancements in intelligent computing, offering both foundational knowledge and practical insights. It is designed to serve as a valuable resource for students, researchers, and professionals seeking to understand and apply IC techniques in real-world scenarios.
Showcases recent, impactful applications of intelligent computing across diverse domains, supported by detailed case studies.
Offers deep insights into the latest research developments and outlines promising areas for future exploration in intelligent computing.
Combines theoretical foundations with algorithmic, simulation-based, and implementation-oriented research to provide a holistic understanding of IC systems.
Balances foundational theory for beginners with practical simulations and real-life implementations for intermediate and advanced readers.
Contents
Chapter 1: A Review on Global Land Use/Land Cover Change Analysis using Digital Image Processing
Chapter 2: Reduction of Two-Dimensional Data for Speeding up Convex Hull Computation
Chapter 3: Enhancing Brain Tumor Detection with an Ensemble Model
Chapter 4: Optical Character Recognition -Based Intelligent Grading System for Handwritten Text
Chapter 5: Quantum-Inspired Neural Networks: Bridging Quantum Computing and Deep Learning for Next-Generation AI Systems
Chapter 6: Deep Learning-Based Approach for Robust Image Authentication
Chapter 7: AI-driven Autonomous Cyber Threat Intelligence (CTI) Curation and Lifecycle Management
Chapter 8: Enhancing Brain Tumor Classification Using Transfer Learning and Convolutional Neural Networks
Chapter 9: Real-Time Feedback for Teachers using Multi modal Emotion Detection in Classroom Teaching
Chapter 10: Enhanced Approach for Chronic Disease Diagnosis and Prediction using Ensemble Deep Learning
Chapter 11: Empowering Industry 5.0 with Large Language Models for Phishing Defense
Chapter 12: AI-Generated Text Detection: A Hybrid CNN-BiLSTM and BERT-Based Large Language Model Approach
Chapter 13: Swarm Intelligence Algorithms for Autonomous Robotics in Unknown and Dynamic Environments
Chapter 14: Classification of Sleep Stage for Human Wellness from Single-Channel EEG using Convolutional Neural Network of Deep Learning
Chapter 15: Minimum Flow Rates Maximization using Graph Conversion Techniques In Rechargeable Wireless Sensor Networks (rWSN) of IoT
Chapter 16: Explainable Transformer-Augmented U-Net for Brain Tumor Segmentation in MRI
Chapter 17: CycleGAN-Based MRI-to-CT Image Synthesis for Tumor-Centric Medical Image Translation
Chapter 18: Preprocessing in Colorectal Cancer Histopathology: A Prerequisite for Effective Computational Analysis
Chapter 19: A Hybrid Machine Learning Approaches for Detecting Intrusions in Wireless Sensor Networks (WSN)
