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Neuro-Symbolic Artificial Intelligence Concepts and Applications

206,99 €

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Beschreibung

Produktdetails

Einband

Gebundene Ausgabe

Erscheinungsdatum

17.08.2026

Herausgeber

R. Nidhya + weitere

Verlag

John Wiley & Sons

Seitenzahl

400

Sprache

Englisch

ISBN

978-1-394-35557-0

Beschreibung

Produktdetails

Einband

Gebundene Ausgabe

Erscheinungsdatum

17.08.2026

Herausgeber

Verlag

John Wiley & Sons

Seitenzahl

400

Sprache

Englisch

ISBN

978-1-394-35557-0

Herstelleradresse

Libri GmbH
Europaallee 1
36244 Bad Hersfeld
DE

Email: GPSR Kontakt

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  • Produktbild: Neuro-Symbolic Artificial Intelligence

  • Series Preface xv
    Preface xvii
    Acknowledgements xxi

    Part 1: Neuro-Symbolic AI: Concepts 1

    1 Cataract Detection Systems Using Deep Learning Technique: A Survey 3
    Arveti Mallikharjuna Rao and Suma Kamalesh Gandhimathi

    1.1 Introduction 4
    1.2 Deep Learning Models 6
    1.3 Conclusion and Future Work 14

    2 Agentic AI Workflows for Financial Large Language Models Using LlaMA and LangChain Framework 19
    Mantri Udaya Jyothi, John Deva Prasanna D. S., Shanthini A. and Balasubramani S.

    2.1 Introduction 20
    2.2 Predict Stock Using Financial Analysis 21
    2.3 Stock Market Prediction Using Agentic AI Using LLM 23
    2.4 Llama Framework 24
    2.5 Llama Framework Reduces AI Trading Risks 27
    2.6 Working Principle of Agents 28
    2.7 Results 33
    2.8 Conclusion 36

    3 Brain-Inspired Artificial Neural Network for Energy-Efficient and Adaptive Learning 39
    R. Dhanalakshmi, Sahaya Beni Prathiba, Kavisankar L., Balasubramani S. and Pandiyanathan M.

    3.1 Introduction 40
    3.2 Literature Review 40
    3.3 Methodology 42
    3.4 Proposed System 46
    3.5 Simulation Results 50
    3.6 Conclusion 54

    4 Neuro-Symbolic AI with a CNN-Based Framework for Detecting Tomato Leaf Diseases 59
    Khaleelullah Shaik and Mohammed Ali Shaik

    4.1 Introduction 60
    4.2 Related Work 62
    4.3 Methodology 66
    4.4 Performance Analysis 72
    4.5 Conclusion 75

    5 Early Detection of Breast Cancer Using Multi-Modal Deep Learning Framework 79
    Salma Mohammad and Mohammed Ali Shaik

    5.1 Introduction 80
    5.2 Related Work 81
    5.3 Methodology 83
    5.4 Results and Discussion 90
    5.5 Conclusion 97

    6 Neuro-Symbolic Transfer Learning Model with Logic-Based Intrusion Detection System in IoT 101
    Deepak V., S. John Justin Thangaraj, Yogaraja C. A. and Iswariya S.

    6.1 Introduction 102
    6.2 Literature Review 104
    6.3 Neuro-Symbolic Transfer Learning + BiLSTM Model 107
    6.4 Results and Discussion 114
    6.5 Conclusion 118

    7 Integrating Artificial Intelligence in Neuro-Symbolic: Challenges, Applications, and Future Directions 121
    J. D. Dorathi Jayaseeli, D. Malathi, R. S. Ponmagal, G. Abirami, S. Nagadevi and M. Senthil Raja

    7.1 Introduction 122
    7.2 Neuro-Symbolic AI: An Overview 123
    7.3 Evolution of Neuro-Symbolic AI 125
    7.4 Neural-Symbolic Integration 126
    7.5 Applications of Neuro-Symbolic AI 129
    7.6 Challenges and Future Directions in Neuro-Symbolic AI 135
    7.7 Conclusion 137

    Part 2: Neuro-Symbolic AI: Applications 143

    8 A Rule-Based Decision Framework for Accident Prevention in Intelligent Transport Systems 145
    D. Pavithra, T. Deepa, Shaik Naseema, R. Nidhya, G. Smilarubavathy and C. Kumar

    8.1 Introduction 146
    8.2 Related Work 147
    8.3 Rule-Based Accident Prevention System 151
    8.4 Simulation Results 160
    8.5 Conclusion 163

    9 A Hybrid Logic-Driven and Neural Parsing Framework for Enhanced Emotion Recognition in Natural Language Processing 167
    R. Nidhya, V. Arun, T. Maragatham, D. J. Ashpin Pabi, Ajaypradeep N. and Manish Kumar

    9.1 Introduction 168
    9.2 Literature Review 170
    9.3 Methodology 173
    9.4 Results and Discussion 179
    9.5 Conclusion 185

    10 A Neuro-Symbolic AI Approach for Lumbar Spinal Stenosis Detection Using Graph Convolutional Networks and Fuzzy Logic 189
    Gurusamy Murugesan, Sabenabanu Abdulkadhar, Selvamuthukumar T., Velkumar K. and Rajkumar K.

    10.1 Introduction 190
    10.2 Materials and Methods 191
    10.3 Results and Discussion 198
    10.4 Conclusion and Future Work 202

    11 Adaptive Filtering Framework for Medical Image Denoising across Spatial and Wavelet Filters 207
    Naveen Kumar Penjarla, Tejaswi Vallabhapurapu, Syamala Rao P., Nissankara Lakshmi Prasanna, Kamesh Sonti and P. Vishnu Priya

    11.1 Introduction 208
    11.2 Literature Review 211
    11.3 Methodology 212
    11.4 Results and Discussion 215
    11.5 Conclusion 222

    12 Heritage Monument Classification Using Hybrid Deep Attention-Based Architecture for Cultural Preservation 225
    A. Satya Phani Kumari, Kalai Vani Y.S., Savitha S., Sujata Kulkarni and Jyothi N. M.

    12.1 Introduction 226
    12.2 Literature Survey 227
    12.3 Methodology 229
    12.4 Experimentation 233
    12.5 Results 235
    12.6 Discussion 239
    12.7 Conclusion 241

    13 Comparative Analysis and Classification of Age-Related Medical Conditions Applying Neural Network and Transformer-Based Deep Models 245
    Levina Tukaram, Umme Najma, D. Chandravathi, Bh. Padma and Jyothi N. M.

    13.1 Introduction 246
    13.2 Literature Survey 247
    13.3 Methodology 250
    13.4 Experimentation 253
    13.5 Results 255
    13.6 Discussion 259
    13.7 Conclusion and Future Enhancements 265

    14 Integrating Locality Sensitive Hashing and Embeddings into Collaborative Filtering for the Visual-Image-Based View 269
    Balaji Maram, Rekha Sundari, Anupama Angadi, Satya Keerthi Gorripati and Venubabu Rachapudi

    14.1 Introduction 270
    14.2 Related Works 271
    14.3 Methodology 273
    14.4 Experimental Results and Analysis 283
    14.5 Conclusion 287

    15 Adversarial Architectures and BERT for Mitigating Gender Bias in Word Embeddings towards Ethical AI Systems 291
    Saraswathi Rangaraju, P. Lakshmilavanya, Karunsagar Kanda, Bh. Padma, Kothapalli Ramesh Chandra and Jyothi N. M.

    15.1 Introduction 292
    15.2 Literature Survey 293
    15.3 Methodology 295
    15.4 Results 303
    15.5 Discussion 310
    15.6 Conclusion 312

    16 Exploring Machine Learning in Voice-Based Parkinson's Disease Diagnosis: A Comprehensive Survey 317
    G. Smilarubavathy and K. Vijayakumar

    16.1 Introduction 318
    16.2 Background 318
    16.3 Flowchart 319
    16.4 Performance Metrics 323
    16.5 Comparative Analysis 324
    16.6 Challenges and Limitations 327
    16.7 Future Directions 329

    17 Neuro-AI-Driven Image Augmentation and Data Leak Prevention via Automated Classification Agents 337
    S. M. Keerthana and K. Vijayakumar

    17.1 Introduction 338
    17.2 Background 339
    17.3 Methods 346
    17.3.1 Preprocessing and Automatic Annotating 346
    17.4 Result 349

    Conclusion 352
    References 352
    Index 355