Recent Trends in Computational Intelligence Enabled Research Theoretical Foundations and Applications
Coordonnateurs : Bhattacharyya Siddhartha, Dutta Paramartha, Samanta Debabrata, Mukherjee Anirban, Pan Indrajit
The field of computational intelligence has grown tremendously over that past five years, thanks to evolving soft computing and artificial intelligent methodologies, tools and techniques for envisaging the essence of intelligence embedded in real life observations. Consequently, scientists have been able to explain and understand real life processes and practices which previously often remain unexplored by virtue of their underlying imprecision, uncertainties and redundancies, and the unavailability of appropriate methods for describing the incompleteness and vagueness of information represented. With the advent of the field of computational intelligence, researchers are now able to explore and unearth the intelligence, otherwise insurmountable, embedded in the systems under consideration. Computational Intelligence is now not limited to only specific computational fields, it has made inroads in signal processing, smart manufacturing, predictive control, robot navigation, smart cities, and sensor design to name a few.
Recent Trends in Computational Intelligence Enabled Research: Theoretical Foundations and Applications explores the use of this computational paradigm across a wide range of applied domains which handle meaningful information. Chapters investigate a broad spectrum of the applications of computational intelligence across different platforms and disciplines, expanding our knowledge base of various research initiatives in this direction. This volume aims to bring together researchers, engineers, developers and practitioners from academia and industry working in all major areas and interdisciplinary areas of computational intelligence, communication systems, computer networks, and soft computing.
2. Computational intelligence techniques for localization and clustering in wireless sensor
3. Computational intelligent techniques for resource management schemes in wireless sensor networks
4. Swarm intelligence based MSMOPSO for optimization of resource provisioning in Internet of Things
5. DNA-based authentication to access internet of things-based healthcare data
6. Computational intelligence techniques for cancer diagnosis
7. Security and privacy in the internet of things: computational intelligent techniques-based approaches
8. Automatic enhancement of coronary arteries using convolutional gray-level templates and path-based metaheuristics
9. Smart city development: Theft handling of public vehicles using image analysis and cloud network
10. Novel detection of cancerous cells through an image segmentation approach using principal component analysis
11. Classification of the operating spectrum for the RAMAN amplifier embedded optical communication system using soft computing techniques
12. Random walk elephant swarm water search algorithm for identifying order-preserving submatrices in gene expression data: a new approach using elephant swarm water search algorithm
13. Geopositioning of fog nodes based on user device location and framework for game theoretic applications in an fog to cloud network
14. A wavelet-based low frequency prior for single-image dehazing
15. Segmentation of retinal blood vessel structure based on statistical distribution of the area of isolated objects
16. Energy-efficient rendezvous point-based routing in wireless sensor network with mobile sink
17. An integration of handcrafted features for violent event detection in videos
18. Deep learning-based diabetic retinopathy detection for multiclass imbalanced data
19. Internet of Things e-health revolution: secured transmission of homeopathic e-medicines through chaotic key formation
20. Smart farming and water saving-based intelligent irrigation system implementation using the Internet of Things
21. Intelligent and smart enabling technologies in advanced applications: recent trends
22. Leveraging technology for healthcare and retaining access to personal health data to enhance personal health and well-being
23. Enhancement of foveolar architectural changes in gastric endoscopic biopsies
Dr. Paramartha Dutta did his Bachelors and Masters in Statistics from the Indian Statistical Institute, Calcutta in the years 1988 and 1990 respectively. He afterwards completed his Master of Technology in Computer science from the same Institute in the year 1993 and Doctor of Philosophy in Engineering from the Bengal Engineering and Science University, Shibpur in 2005 respectively. He has served in the capacity of research personnel in various projects funded by Govt. of India, which include DRDO, CSIR, Indian Statistical Institute, Calcutta etc. Dr. Dutta is now a Professor in the Department of Computer and system Sciences of the Visva Bharati University, West Bengal, India. Prior to this, he served Kalyani Government Engineering College and College of Engineering in West Bengal as full time faculty members. He has coauthored four books and has also one edited book to his credit. He has pub
- Provides insights into the theory, algorithms, implementation, and application of computational intelligence techniques
- Covers a wide range of applications of deep learning across various domains which are researching the applications of computational intelligence
- Investigates novel techniques and reviews the state-of-the-art in the areas of machine learning, computer vision, soft computing techniques
Date de parution : 08-2021
Ouvrage de 418 p.
15.2x22.8 cm
