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Computational Intelligence for Information Retrieval

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advanced neural network models for retrieval
Age Group_Uncategorized
Age Group_Uncategorized
Ai
AR
automatic traffic accident detection
automatic-update
B01=Dharmender Saini
B01=Gopal Chaudhary
B01=Vedika Gupta
Big Data
Big Data Security
biometric authentication
Category1=Non-Fiction
Category=UYQ
CBIR
CBIR Technique
CF
cloud data protection
cloud platforms
CNN Architecture
CNN Model
Computational Intelligence
Computational Intelligence Methods
Construct Feature Vector
content-based image retrieval
Convolutional Layer
convolutional neural networks
COP=United Kingdom
deep learning
deep learning applications
Delivery_Delivery within 10-20 working days
diabetic retinopathy disease
dynamic histogram equalization
emotion prediction
Emotiv EPOC
eq_bestseller
eq_computing
eq_isMigrated=2
eq_nobargain
eq_non-fiction
Finger Vein
finger vein feature extraction
fuzzy-based approach
gender recognition
hybrid computational intelligence
image enhancement
Language_English
machine learning
Max Pooling Layers
medical image analysis
melanoma tumor
Membership Function
Ml Model
mood detection
PA=Available
pattern recognition
pattern recognition methods
POS Tag
Price_€50 to €100
PS=Active
QR Code
Random Forest
Recommendation System
sentiment analysis techniques
smartphones
softlaunch
song recommendation
SVM Classification Model
SVM Classifier
Vein Image

Product details

  • ISBN 9780367680831
  • Weight: 460g
  • Dimensions: 156 x 234mm
  • Publication Date: 07 Oct 2024
  • Publisher: Taylor & Francis Ltd
  • Publication City/Country: GB
  • Product Form: Paperback
  • Language: English
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Description

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.
About

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.