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Applied Computer Vision and Soft Computing with Interpretable AI

Applied Computer Vision and Soft Computing with Interpretable AI

          
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About the Book

This reference text presents the knowledge base of computer vision and soft computing techniques with their applications for sustainable developments. Features: Covers a variety of deep learning architectures useful for computer vision tasks Demonstrates the use of different soft computing techniques and their applications for different computer vision tasks Highlights the unified strengths of hybrid techniques based on deep learning and soft computing taken together that give the interpretable, adaptive, and optimized solution to a given problem Addresses the different issues and further research opportunities in computer vision and soft computing Describes all the concepts with practical examples and case studies with appropriate performance measures that validate the applicability of the respective technique to a certain domain Considers recent real word problems and the prospective solutions to these problems This book will be useful to researchers, students, faculty, and industry personnel who are eager to explore the power of deep learning and soft computing for different computer vision tasks.

Table of Contents:
1. Improved Healthcare System using Artificial Intelligence: Technology and Challenges. 2. A brain MRI segmentation method using feature weighting and a combination of efficient visual features. 3. Vision Based Skin Cancer Detection: Various Approaches with Comparative study. 4. MentoCare: An Improved Mental Healthcare System for Public. 5. Employee Health monitoring system using WBANs and Machine Learning. 6. Monitoring operational parameters in manufacturing industry using web analytical dashboards. 7. Concurrent Line Perpendicular Distance Functions for Contour Points Analysis. 8. A Resemblance of Convolutional Neural Network Architectures for Classifying Ferrograph Images. 9. Role of AI and IoT in Smart Agriculture towards Green Engineering. 10. Intuitionistic Fuzzy Hyper Graph with their Operations. 11. Heterogeneous Multiple-mini–Graphs Neural Network based Spammer Detection. 12. Spam email classification using Meta-Heuristic Algorithm. 13. A Blockchain Model for Land Registration Properties in Metro Cities. 14. A review on sentiment analysis applications and challenges. 15. Handling Skewed Datasets in Computing Environments: The Classifier Ensemble Approach. 16. Diagnosis of Dementia Using MRI: A Machine Learning Approach. 17. Optimized Tolerance Based Student’s Face Recognition and Identification Using Deep Learning. 18. Impact of Fake News on Society with Detection and Classification Techniques. 19. Neurological Disorder Detection Using Computer Vision and Machine Learning Technique. 20. Deep Learning for Tea Leaf Disease Classification: Challenges, Study Gaps, and Emerging Technologies.


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Product Details
  • ISBN-13: 9781032417264
  • Publisher: Taylor & Francis Ltd
  • Publisher Imprint: Chapman & Hall/CRC
  • Height: 254 mm
  • No of Pages: 316
  • Width: 178 mm
  • ISBN-10: 1032417269
  • Publisher Date: 26 May 2025
  • Binding: Paperback
  • Language: English
  • Weight: 630 gr


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