Generative AI stands at the forefront of artificial intelligence innovation, redefining the capabilities of machines to create, imagine, and innovate. GAI explores the domain of creative production with new and original content across various forms, including images, text, music, and more. In essence, generative AI stands as evidence of the boundless potential of artificial intelligence, transforming industries, sparking creativity, and challenging conventional paradigms. It represents not just a technological advancement but a catalyst for reimagining how machines and humans collaborate, innovate, and shape the future.

The book examines real-world examples of how generative AI is being used in a variety of industries. The first section explores the fundamental concepts and ethical considerations of generative AI. In addition, the section also introduces machine learning algorithms and natural language processing. The second section introduces novel neural network designs and convolutional neural networks, providing dependable and precise methods. The third section explores the latest learning-based methodologies to help researchers and farmers choose optimal algorithms for specific crop and hardware needs. Furthermore, this section evaluates significant advancements in revolutionizing online content analysis, offering real-time insights into content creation for more interactive processes.

Audience
The book will be read by researchers, engineers, and students working in artificial intelligence, computer science, and electronics and communication engineering as well as industry application areas.

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Yes, you can access Generative Artificial Intelligence by R. Nidhya,D. Pavithra,Manish Kumar,A. Dinesh Kumar,S. Balamurugan in PDF and/or ePUB format, as well as other popular books in Computer Science & Artificial Intelligence (AI) & Semantics. We have over one million books available in our catalogue for you to explore.

Information

Publisher

Year

Print ISBN

eBook ISBN

Edition

Topic

Computer Science

Subtopic

Artificial Intelligence (AI) & Semantics

Index

Computer Science

Cover
Series Page
Title Page
Copyright Page
Contents
Preface
Chapter 1 Exploring the Creative Frontiers: Generative AI Unveiled
Chapter 2 An Efficient Infant Cry Detection System Using Machine Learning and Neuro Computing Algorithms
Chapter 3 Improved Brain Tumor Segmentation Utilizing a Layered CNN Model
Chapter 4 Natural Language Processing in Generative Adversarial Network
Chapter 5 Modeling A Deep Learning Network Model for Medical Image Panoptic Segmentation
Chapter 6 A Hybrid DenseNet Model for Dental Image Segmentation Using Modern Learning Approaches
Chapter 7 Modeling A Two-Tier Network Model for Unconstraint Video Analysis Using Deep Learning
Chapter 8 Detection of Peripheral Blood Smear Malarial Parasitic Microscopic Images Utilizing Convolutional Neural Network
Chapter 9 Exploring the Efficacy of Generative AI in Constructing Dynamic Predictive Models for Cybersecurity Threats: A Research Perspective
Chapter 10 Poultry Disease Detection: A Comparative Analysis of CNN, SVM, and YOLO v3 Algorithms for Accurate Diagnosis
Chapter 11 Generative AI-Enhanced Deep Learning Model for Crop Type Analysis Based on Clustered Feature Vectors and Remote Sensing Imagery
Chapter 12 Cardiovascular Disease Prediction with Machine Learning: An Ensemble-Based Regressive Neighborhood Model
Chapter 13 Detection of IoT Attacks Using Hybrid RNN-DBN Model
Chapter 14 Identification of Foliar Pathologies in Apple Foliage Utilizing Advanced Deep Learning Techniques
Chapter 15 Enhancing Cloud Security Through AI-Driven Intrusion Detection Utilizing Deep Learning Methods and Autoencoder Technology
Chapter 16 YouTube Comment Analysis Using LSTM Model
Index
Also of Interest
EULA

About this book

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Table of contents