Integrating Neurocomputing with Artificial Intelligence

Abhishek Kumar, Pramod Singh Rathore, Sachin Ahuja, Umesh Kumar Lilhore

• Publisher: Wiley-Scrivener
• Year: 2025
• Print ISBN: 9781394335688
• eBook ISBN: 9781394335701
• Edition: 1
• Topic: Technik & Maschinenbau
• Subtopic: Robotertechnik

Integrating Neurocomputing with Artificial Intelligence provides unparalleled insights into the cutting-edge convergence of neuroscience and computing, enriched with real-world case studies and expert analyses that harness the transformative potential of neurocomputing in various disciplines.

Integrating Neurocomputing with Artificial Intelligence is a comprehensive volume that delves into the forefront of the neurocomputing landscape, offering a rich tapestry of insights and cutting-edge innovations. This volume unfolds as a carefully curated collection of research, showcasing multidimensional perspectives on the intersection of neuroscience and computing. Readers can expect a deep exploration of fundamental theories, methodologies, and breakthrough applications that span the spectrum of neurocomputing.

Throughout the book, readers will find a wealth of case studies and real-world examples that exemplify how neurocomputing is being harnessed to address complex challenges across different disciplines. Experts and researchers in the field contribute their expertise, presenting in-depth analyses, empirical findings, and forward-looking projections. Integrating Neurocomputing with Artificial Intelligence serves as a gateway to this fascinating domain, offering a comprehensive exploration of neurocomputing's foundations, contemporary developments, ethical considerations, and future trajectories. It embodies a collective endeavor to drive progress and unlock the potential of neurocomputing, setting the stage for a future where artificial intelligence is not merely artificial, but profoundly inspired by the elegance and efficiency of the human brain.

Table of contents

• Cover
• Series Page
• Title Page
• Copyright Page
• Contents
• Foreword
• Preface
• Chapter 1 Integrating Fog Computing with AI Model on Decision Making for Distribution of Energy Management
• Chapter 2 Construction and Simulation of Hybrid Neural Network and LSTM to Language Process Model
• Chapter 3 An Approach to Ensure the Safety of Industry 4.0 Mobile Robots
• Chapter 4 Feature Extrusion and Categorization of Disease by Hybrid Neuro-Fuzzy Computing
• Chapter 5 AI Based Neuromorphic Vision to Control the Robotic Drilling Machine
• Chapter 6 Design and Development of AI Neuromorphic to Control the Autonomous Driving System
• Chapter 7 Design of Brain-Computer Interface System to Develop Humanoid Robot
• Chapter 8 AI-Based Neural Network Used to Enhance the Decision-Making System to Improve Operational Performance
• Chapter 9 Simulation and Implementation of English Speech Recognition by NLP
• Chapter 10 Deep Learning-Based Neuro Computing to Classify and Diagnosis of Ophthalmology by OCT
• Chapter 11 Deep CNN-Based Multi-Image Steganography: Private Key
• Chapter 12 Automatic Classification of Honey Bee Subspecies by AI-Based Neural Network
• Chapter 13 Acoustic Modeling and Evaluation of Speech Recognition by Neural Networks
• Chapter 14 Brain–Computer Interface for Humanoid Robot Control Adaptation
• Chapter 15 Evaluation and Validation of Type 1 Diabetes Clinical Data by GAN
• Chapter 16 Exploring Neuromorphic Computing with Deep Learning: Unveiling Opportunities, Applications, and Overcoming Challenges
• Chapter 17 Quantum Neurocomputing: Bridging the Frontiers of Quantum Computing and Neural Networks
• Index
• Also of Interest
• EULA