Cognitive Computing in Human Cognition

Perspectives and Applications

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

Serie: Learning and Analytics in Intelligent Systems 17

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
Vår pris
1856,-

(Innbundet) Fri frakt!
Leveringstid: Sendes innen 21 dager
På grunn av Brexit-tilpasninger og tiltak for å begrense covid-19 kan det dessverre oppstå forsinket levering.

Innbundet
Legg i
Innbundet
Legg i
Vår pris: 1856,-

(Innbundet) Fri frakt!
Leveringstid: Sendes innen 21 dager
På grunn av Brexit-tilpasninger og tiltak for å begrense covid-19 kan det dessverre oppstå forsinket levering.

Om boka

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

Innholdsfortegnelse

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.