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Handbook of research on machine learning techniques for pattern recognition and information security / Mohit Dua, Ankit Kumar Jain, editors. — 1 online resource (26 PDFs (355 pages)) — <URL:http://elib.fa.ru/ebsco/2939945.pdf>.

Record create date: 5/30/2021

Subject: Database security.; Machine learning.; Pattern recognition systems.; Pattern recognition systems.; Machine learning.; Database security.

Collections: EBSCO

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"This book examines the impact of machine learning techniques on pattern recognition and information security"--.

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Table of Contents

  • Cover
  • Title Page
  • Copyright Page
  • Book Series
  • Editorial Advisory Board
  • List of Contributors
  • Table of Contents
  • Detailed Table of Contents
  • Foreword
  • Preface
  • Chapter 1: Intelligent Vision-Based Systems for Public Safety and Protection via Machine Learning Techniques
  • Chapter 2: Comparative Analysis of Various Soft Computing Technique-Based Automatic Licence Plate Recognition Systems
  • Chapter 3: Impact of Syntactical and Statistical Pattern Recognition on Prognostic Reasoning
  • Chapter 4: Challenges and Issues in Plant Disease Detection Using Deep Learning
  • Chapter 5: Automatic Animal Detection and Collision Avoidance System (ADCAS) Using Thermal Camera
  • Chapter 6: Distracted Driver Detection System Using Deep Learning Technique
  • Chapter 7: Application of Deep Learning Model Convolution Neural Network for Effective Web Information Retrieval
  • Chapter 8: Cosine Transformed Chaos Function and Block Scrambling-Based Image Encryption
  • Chapter 9: An Improved Approach for Multiple Image Encryption Using Alternate Multidimensional Chaos and Lorenz Attractor
  • Chapter 10: Simple Linear Iterative Clustering (SLIC) and Graph Theory-Based Image Segmentation
  • Chapter 11: COVID-19 Detection Using Chest X-Ray and Transfer Learning
  • Chapter 12: COVID-19-Related Predictions Using NER on News Headlines
  • Chapter 13: Security Issues in Fog Computing and ML-Based Solutions
  • Chapter 14: Intrusion Detection Systems
  • Chapter 15: Vulnerability Assessment and Malware Analysis of Android Apps Using Machine Learning
  • Chapter 16: Locally-Adaptive Naïve Bayes Framework Design via Density-Based Clustering for Large Scale Datasets
  • Chapter 17: RFID Security Issues, Defenses, and Security Schemes
  • Compilation of References
  • About the Contributors
  • Index

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