Research Advances in Intelligent Computing

Anshul Verma, Pradeepika Verma, Kiran Kumar Pattanaik, Lalit Garg, Anshul Verma, Pradeepika Verma, Kiran Kumar Pattanaik, Lalit Garg

• Publisher: CRC Press
• Year: 2023
• Print ISBN: 9781032340517
• eBook ISBN: 9781000835939
• Topic: Computer Science
• Subtopic: Business Intelligence
• Index: Computer Science

Since the invention of computers and other similar machines, scientists and researchers have been trying very hard to enhance their capabilities to perform various tasks. As a result, the capabilities of computers are growing exponentially day by day in terms of diverse working domains, versatile jobs, processing speed, and reduced size. Now, we are in the race to make these machines as intelligent as human beings. Artificial intelligence (AI) came up as a way of making a computer or computer software think in a similar manner to the way that humans think. AI is inspired by the study of human brain, including how humans think, learn, decide, and act while trying to solve a problem. The outcomes of this study are the basis of developing intelligent software and systems or intelligent computing (IC).

An IC system has the capabilities of reasoning, learning, problem-solving, perception, and linguistic intelligence. IC systems consist of AI techniques as well as other emerging techniques that make a system intelligent. The use of IC has been seen in almost every sub-domain of computer science such as networking, software engineering, gaming, natural language processing, computer vision, image processing, data science, robotics, expert systems, and security. Nowadays, IC is also useful for solving various complex problems in diverse domains such as for predicting disease in medical science, predicting land fertility or crop productivity in agricultural science, predicting market growth in economics, and weather forecasting.

For all these reasons, this book presents the advances in AI techniques, under the umbrella of IC. In this context, the book includes recent research that has been done in the areas of machine learning, neural networks, deep learning, evolutionary algorithms, genetic algorithms, swarm intelligence, fuzzy systems, and so on. This book discusses recent theoretical, algorithmic, simulation, and implementation-based advancements related to IC.

Table of contents

• Cover Page
• Half-Title Page
• Title Page
• Copyright Page
• Contents
• Preface
• Acknowledgments
• About the Editors
• List of Contributors
• Chapter 1 RNN-Based Machine Translation for Indian Languages
• Chapter 2 Dynamic Movie Ticket Price Prediction Using Machine Learning
• Chapter 3 Designing a GUI for Offline Text-Independent Writer Identification System
• Chapter 4 Soil Fertility Prediction Using a Soft Computing Approach
• Chapter 5 Psychological Distress Detection, Classification and Assistance Using AI
• Chapter 6 Fast and Efficient Text Searching in Compressed Data Using Burrows–Wheeler Transform
• Chapter 7 A Comprehensive Exploration of Brain Tumor Segmentation Using Deep Learning Techniques
• Chapter 8 Hand Sign Recognition Using LeNet-like Architecture
• Chapter 9 Automated Kinship Recognition through Facial Feature Matching
• Chapter 10 Ensemble Convolutional Neural Network: A Bidimensional EMD Model for ECG Denoising
• Chapter 11 Wrapper-Based Feature Selection for Big Data Using a Multi-Core Environment
• Chapter 12 MDAKB: A Metadata-Driven Approach for Multilingual Knowledge Base Generation for Agricultural Domains in the Indian Context
• Chapter 13 Melanoma Prediction from Skin Lesions Using Convolutional Neural Network against the Support Vector Machine Learning Algorithm to Achieve Maximum Accuracy and Minimum Loss
• Chapter 14 Fusion-Based Morphological Watershed Segmentation Algorithm for Medical Images
• Chapter 15 Music Recommendation System to Address the Problem of Long Tail Using Multi-Stage Graph
• Chapter 16 Speech-Based Access of Agricultural Commodity Prices and Weather Information in the Kannada Language and Its Dialects
• Chapter 17 Weather Classification: Image Embedding Using Convolutional Autoencoder and Predictive Analysis Based on Stacked Generalization
• Chapter 18 COVID-19 Confirmed Case Prediction after Vaccination Using Deep Learning Models
• Chapter 19 Recognition Model for Facial Expression Using Machine Learning
• Chapter 20 Sentiment Analysis and Sarcasm Detection in Indian General Election Tweets
• Chapter 21 Image Generation Using Deep Convolutional Generative Adversarial Networks
• Chapter 22 Human Activity Identification Using Artificial Intelligence
• Chapter 23 Heartbeat-Based Failure Detector of Perfect P Class for Synchronous Hierarchical Distributed Systems
• Index