1  Cover

      2  Title Page

      3  Copyright

      4  Preface

      5  1 Machine Learning-Based Virus Type Classification Using Transmission Electron Microscopy Virus Images 1.1 Introduction 1.2 Related Works 1.3 Methodology 1.4 Results and Discussion 1.5 Conclusion References

      6  2 Capsule Networks for Character Recognition in Low Resource Languages 2.1 Introduction 2.2 Background Study 2.3 System Design 2.4 Experiments and Results 2.5 Discussion References

      7  3 An Innovative Extended Method of Optical Pattern Recognition for Medical Images With Firm Accuracy—4f System-Based Medical Optical Pattern Recognition 3.1 Introduction 3.2 Optical Signal Processing 3.3 Extended Medical Optical Pattern Recognition 3.4 Initial 4f System 3.5 Simulation Output 3.6 Complications in Real Time Implementation 3.7 Future Enhancements References

      8  4 Brain Tumor Diagnostic System— A Deep Learning Application 4.1 Introduction 4.2 Deep Learning 4.3 Brain Tumor Diagnostic System 4.4 Computer-Aided Diagnostic Tool 4.5 Conclusion and Future Enhancements References

      9  5 Machine Learning for Optical Character Recognition System 5.1 Introduction 5.2 Character Recognition Methods 5.3 Phases of Recognition System 5.4 Post-Processing 5.5 Performance Evaluation 5.6 Applications of OCR Systems 5.7 Conclusion and Future Scope References

      10  6 Surface Defect Detection Using SVM-Based Machine Vision System with Optimized Feature 6.1 Introduction 6.2 Methodology 6.3 Conclusion References

      11  7 Computational Linguistics-Based Tamil Character Recognition System for Text to Speech Conversion 7.1 Introduction 7.2 Literature Survey 7.3 Proposed Approach 7.4 Design and Analysis 7.5 Experimental Setup and Implementation 7.6 Conclusion References

      12  8 A Comparative Study of Different Classifiers to Propose a GONN for Breast Cancer Detection 8.1 Introduction 8.2 Methodology 8.3 Results and Discussion 8.4 Conclusion References

      13  9 Mexican Sign-Language Static-Alphabet Recognition Using 3D Affine Invariants 9.1 Introduction 9.2 Pattern Recognition 9.3 Experiments 9.4 Results 9.5 Discussion 9.6 Conclusion Acknowledgments References

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