Computational Intelligence for Information Retrieval (eBook, ePUB)

Redaktion: Saini, Dharmender; Gupta, Vedika; Chaudhary, Gopal

• Format: ePub

Produktbeschreibung

This book provides a thorough understanding of the integration of computational intelligence with information retrieval including content-based image retrieval using intelligent techniques, hybrid computational intelligence for pattern recognition, intelligent innovative systems, and protecting and analysing big data on cloud platforms. The book aims to investigate how computational intelligence frameworks are going to improve information retrieval systems. The emerging and promising state-of-the-art of human-computer interaction is the motivation behind this book.

The book covers a wide range of topics, starting from the tools and languages of artificial intelligence to its philosophical implications, and thus provides a plethora of theoretical as well as experimental research, along with surveys and impact studies.

Further, the book aims to showcase the basics of information retrieval and computational intelligence for beginners, as well as their integration, and challenge discussions for existing practitioners, including using hybrid application of augmented reality, computational intelligence techniques for recommendation systems in big data, and a fuzzy-based approach for characterization and identification of sentiments.

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Produktdetails

• Verlag: Taylor & Francis eBooks
• Seitenzahl: 292
• Erscheinungstermin: 14. Dezember 2021
• Englisch
• ISBN-13: 9781000484724
• Artikelnr.: 62782744

Autorenporträt

Gopal Chaudhary is working as an Assistant Professor in Department of Information Technology, at Bharati Vidyapeeth's College of Engineering, New Delhi. Dharmendra Saini is a Professor in Department of Computer Science & Engineering, at Bharati Vidyapeeth's College of Engineering, New Delhi. Vedika Gupta is an Assistant Professor at Bharati Vidyapeeth's College of Engineering, New Delhi.

Inhaltsangabe

1. Hybrid Computational Intelligence for Pattern Recognition.
2. Secure Image Transmission Using Nested Images.
3. Accist: Automatic Traffic Accident Detection and Notification with
Smartphones.
4. Emotion Prediction through EEG Recordings Using Computational
Intelligence.
5. Finger Vein Feature Extraction Using Contrast Enhancement Dynamic
Histogram Equalization for Image Enhancement.
6. Song Recommendation Using Computational Techniques Based on Mood
Detection.
7. Deep Learning Classification of Retinal Images for the Early Detection
of Diabetic Retinopathy Disease.
8. Protecting and Analyzing Big Data on Cloud Platforms.
9. Using Flutter to Develop a Hybrid Application of Augmented Reality.
10. Computational Intelligence Techniques for Recommendation System in Big
Data.
11. Predicting Melanoma Tumor Size through Machine Learning Approaches.
12. A Fuzzy-Based Approach for Characterization and Identification of
Sentiments.
13. Fingerprint Alterations Type Detection and Gender Recognition Using
Convolutional Neural Networks and Transfer Learning.
14. Content-Based Image Retrieval Using Intelligent Techniques.