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Cognitive Computing in Human Cognition : Perspectives and Applications / edited by Pradeep Kumar Mallick, Prasant Kumar Pattnaik, Amiya Ranjan Panda, Valentina Emilia Balas.
- Format:
- Book
- Series:
- Computer Science (SpringerNature-11645)
- Learning and analytics in intelligent systems 2662-3447 ; 17.
- Learning and Analytics in Intelligent Systems, 2662-3447 ; 17
- Language:
- English
- Subjects (All):
- Artificial intelligence.
- Computational intelligence.
- Automatic control.
- Robotics.
- Mechatronics.
- Biomedical engineering.
- Artificial Intelligence.
- Computational Intelligence.
- Control, Robotics, Mechatronics.
- Biomedical Engineering and Bioengineering.
- Local Subjects:
- Artificial Intelligence.
- Computational Intelligence.
- Control, Robotics, Mechatronics.
- Biomedical Engineering and Bioengineering.
- Physical Description:
- 1 online resource (XIV, 125 pages) : 75 illustrations, 38 illustrations in color.
- Edition:
- First edition 2020.
- Contained In:
- Springer Nature eBook
- Place of Publication:
- Cham : Springer International Publishing : Imprint: Springer, 2020.
- System Details:
- text file PDF
- Summary:
- This edited book designs the Cognitive Computing in Human Cognition to analyze to improve the efficiency of decision making by cognitive intelligence. The book is also intended to attract the audience who work in brain computing, deep learning, transportation, and solar cell energy. Due to this in the recent era, smart methods with human touch called as human cognition is adopted by many researchers in the field of information technology with the Cognitive Computing.
- Contents:
- Chapter 1: Improved Steganography using Odd Even substitution
- Chapter 2: A Tags Mining Approach for Automatic Image Annotation Using Neighbor Images Tree
- Chapter 3: A Survey: Implemented Architectures of 3D Convolutional Neural Networks
- Chapter 4: An approach for detection of dust on solar panels using CNN from RGB dust image to predict power loss
- Chapter 5: A Novel Method of Data Partitioning Using Genetic Algorithm Work Load Driven Approach Utilizing Machine Learning
- Chapter 6: Virtual Dermoscopy using Deep Learning Approach
- Chapter 7: Evaluating Robustness for Intensity Based Image Registration Measures Using Mutual Information and Normalized Mutual Information
- Chapter 8: A New Contrast Based Degraded Document Image Binarization. .
- Other Format:
- Printed edition:
- ISBN:
- 978-3-030-48118-6
- 9783030481186
- Access Restriction:
- Restricted for use by site license.
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