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Cognitive Computing in Human Cognition - 
      Pradeep Kumar Mallick
    
      Prasant Kumar Pattnaik
    
      Amiya Ranjan Panda
    
      Valentina Emilia Balas

Cognitive Computing in Human Cognition

Perspectives and Applications

Pradeep Kumar Mallick (Redaktør) ; Prasant Kumar Pattnaik (Redaktør) ; Amiya Ranjan Panda (Redaktør) ; Valentina Emilia Balas (Redaktør)

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. Les mer
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Paperback
Legg i
Vår pris: 2363,-

(Paperback) Fri frakt!
Leveringstid: Usikker levering*
*Vi bestiller varen fra forlag i utlandet. Dersom varen finnes, sender vi den så snart vi får den til lager

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.
FAKTA
Utgitt:
Forlag: Springer Nature Switzerland AG
Innbinding: Paperback
Språk: Engelsk
Sider: 125
ISBN: 9783030481209
Format: 24 x 16 cm
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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.