Cognitive Computing in Human Cognition: Perspectives and Applications

Author:   Pradeep Kumar Mallick ,  Prasant Kumar Pattnaik ,  Amiya Ranjan Panda ,  Valentina Emilia Balas
Publisher:   Springer Nature Switzerland AG
Edition:   1st ed. 2020
Volume:   17
ISBN:  

9783030481209


Pages:   125
Publication Date:   20 June 2021
Format:   Paperback
Availability:   Manufactured on demand   Availability explained
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Cognitive Computing in Human Cognition: Perspectives and Applications


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Overview

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.

Full Product Details

Author:   Pradeep Kumar Mallick ,  Prasant Kumar Pattnaik ,  Amiya Ranjan Panda ,  Valentina Emilia Balas
Publisher:   Springer Nature Switzerland AG
Imprint:   Springer Nature Switzerland AG
Edition:   1st ed. 2020
Volume:   17
Weight:   0.454kg
ISBN:  

9783030481209


ISBN 10:   3030481204
Pages:   125
Publication Date:   20 June 2021
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Paperback
Publisher's Status:   Active
Availability:   Manufactured on demand   Availability explained
We will order this item for you from a manufactured on demand supplier.

Table of 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. 

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