Advances in Quantum Inspired Artificial Intelligence (eBook, PDF)

Techniques and Applications
Redaktion: Dehuri, Satchidananda; Belciug, Smaranda; Favorskaya, Margarita N.; Chandra Nayak, Sarat; Jena, Monalisa

• Format: PDF

Produktbeschreibung

This book advances the artificial intelligence techniques by strongly inspired from quantum computing. Quantum computing (QC), rooted in the mysterious principles of quantum mechanics, has fascinated scientists, researchers, and visionaries for a long time. Its potential lies in changing how we compute, moving from classical bits to quantum bits (qubits), and unlocking incredible processing capabilities. At the same time, artificial intelligence (AI) has been on a trajectory of rapid advancement, with deep learning becoming proficient at tasks that were once deemed impossible. At this juncture, integrating these two fields through various means can play a pivotal role to bring a technological revolution.

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Produktdetails

• Verlag: Springer Nature Switzerland
• Seitenzahl: 237
• Erscheinungstermin: 2. Juni 2025
• Englisch
• ISBN-13: 9783031899058
• Artikelnr.: 74326083

Inhaltsangabe

1.Quantum-Enhanced Bioinspired Algorithms: An Overview of Optimization and Learning.- 2.Decoding Market Dynamics: Variational Quantum Circuit in Stock Prediction.- 3.Quantum Dot Cellular Automata: Breaking Barriers in Electronics Circuitry for Tomorrow's Technologies.- 4.Quantum Natural Language Processing: Revolutionizing Language Processing.- 5.Quantum Machine Learning in Climate Science and Climate Change Solutions.- 6.Quantum Cloud Computing: Key Technologies, Challenges, and Opportunities.- 7.Security, Privacy, and Trust in Quantum Edge-driven Intelligence: Challenges and Solutions.- 8.Quantum-Inspired Aspect-Based Sentiment Analysis Using Natural Language Processing.- 9.The Applications of Quantum Machine Learning in Today's World.- 10.Unveiling the Role of Internet of Things (IoT) in the Landscape of Quantum Healthcare Monitoring.- 11.Quantum Neural Networks: Exploring Quantum Enhancements in Deep Learning.