Augmented intelligence is an alternate approach of artificial intelligence (AI), which emphasizes AI’s assistive role. Augmented intelligence enhances human skills of reasoning in a robotic system or software by simulating expectancy, educational mining, problem solving, recollection, sequencing, and decision-making capabilities. It is based on a combination of techniques such as machine learning, deep learning and cognitive computing.
This book explains artificial intelligence models that support assistive processes in different situations.
The contributors aim to provide information to a diverse audience with groundbreaking developments in mathematical computing.
The book presents 8 chapters on these topics:
- - Educational data mining in augmented reality virtual learning environment
- - Brain and computer interfaces
- - Tree-based tools for chemometric analysis of infrared spectra
- - Applications of deep learning in medical engineering
- - Bankruptcy prediction model using an enhanced boosting classifier
- - Reputation systems for mobile agent security
- - The crow search algorithm
- - COVID-19 diagnosis and treatment
The contents attempt to integrate various facets of augmented Intelligence, by describing recent research developments and advanced topics of interest to academicians and researchers working on machine learning problems and AI.
Academicians and researchers working on machine learning problems and AI.