Hybrid Computational Intelligence
Challenges and Applications
- 1st Edition - March 5, 2020
- Editors: Siddhartha Bhattacharyya, Vaclav Snasel, Deepak Gupta, Ashish Khanna
- Language: English
- Paperback ISBN:9 7 8 - 0 - 1 2 - 8 1 8 6 9 9 - 2
- eBook ISBN:9 7 8 - 0 - 1 2 - 8 1 8 7 0 0 - 5
Hybrid Computational Intelligence: Challenges and Utilities is a comprehensive resource that begins with the basics and main components of computational intelligence. It brings to… Read more
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Request a sales quoteHybrid Computational Intelligence: Challenges and Utilities is a comprehensive resource that begins with the basics and main components of computational intelligence. It brings together many different aspects of the current research on HCI technologies, such as neural networks, support vector machines, fuzzy logic and evolutionary computation, while also covering a wide range of applications and implementation issues, from pattern recognition and system modeling, to intelligent control problems and biomedical applications. The book also explores the most widely used applications of hybrid computation as well as the history of their development.
Each individual methodology provides hybrid systems with complementary reasoning and searching methods which allow the use of domain knowledge and empirical data to solve complex problems.
- Provides insights into the latest research trends in hybrid intelligent algorithms and architectures
- Focuses on the application of hybrid intelligent techniques for pattern mining and recognition, in big data analytics, and in human-computer interaction
- Features hybrid intelligent applications in biomedical engineering and healthcare informatics
1. Application and Techniques of Opinion Mining
Gupta, Neha, Agrawal, Rashmi
2. Influence of Big Data in Smart Tourism
R, Hanumantha Raju, Sunagar Pramod C., G M Siddesh, Kanavalli Anita, Srinivasa K G
3. Deep learning and its applications for Content-Based Video Retrieval
Hiriyannaiah Srinidhi, Singh Kaushik, H Ashwin, G M Siddesh, Srinivasa K G
4. A Computationally Intelligent agent for detecting fake news using Generative Adversarial networks (GANs)
Hiriyannaiah Srinidhi, Srinivas A.M.D., Shetty Gagan K., G M Siddesh, Srinivasa K G
5. Detection of Primary Glaucoma using ANN with the help of Back Propagation algo in Bio-medical Image Processing
Manjunath T.C.
6. Hybrid Computational Intelligence with Applications to BioMedical Image and HealthCare
Manikandan R.
7. Application of Hybrid Computational Intelligence in Healthcare
Sharma Moolchand, Agrawal Suyash, Deshwal Suman
8. Utility System for premature plant disease detection using machine learning
B J Sowmya, Shetty Chetan, S Seema, Srinivasa K G
9. Artificial Intelligence-Based Computational Fluid Dynamics (CFD) Approaches
Panwar Viswanth
10. Real-Time Video Segmentation using a Vague Adaptive Threshold
Hrishikesh Bhaumik, Siddhartha Bhattacharyya, Susanta Chakraborty
- No. of pages: 250
- Language: English
- Edition: 1
- Published: March 5, 2020
- Imprint: Academic Press
- Paperback ISBN: 9780128186992
- eBook ISBN: 9780128187005
SB
Siddhartha Bhattacharyya
VS
Vaclav Snasel
DG
Deepak Gupta
Dr. Aditya Khamparia has expertise in teaching, entrepreneurship, and research and development of 11 years. He is presently working as Assistant Professor in Babasaheb Bhimrao Ambedkar University, Satellite Centre, Amethi, India. He received his Ph.D. degree from Lovely Professional University, Punjab, India in May 2018. He has completed his M. Tech. from VIT University, Vellore, Tamil Nadu, India and B. Tech. from RGPV, Bhopal, Madhya Pradesh, India. He has completed his PDF from UNIFOR, Brazil. He has published around 105 research papers along with book chapters including more than 25 papers in SCI indexed Journals with cumulative impact factor of above 100 to his credit. Additionally, he has authored and edited eleven books. Furthermore, he has served the research field as a Keynote Speaker/Session Chair/Reviewer/TPC member/Guest Editor and many more positions in various conferences and journals. His research interest include machine learning, deep learning for biomedical health informatics, educational technologies, and computer vision.
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