Book Abstract: In 1971 Dr. Paul C. Lauterbur pioneered spatial information encoding principles that made image formation possible by using magnetic resonance signals. Now Lauterbur, "father of the MRI ...

Thoroughly revised and expanded, this second edition of the popular reference addresses the many important advances that have taken place in the field since the publication of the first edition and ...

Abstract: The penetration of distributed energy resources in electrical grids has been steadily increasing in an effort to reduce greenhouse gas emissions. Inverters, as interfaces between distributed ...

Abstract: Measurements of the equivalent parallel conductance of metal-insulator-semiconductor (MIS) capacitors are shown to give more detailed and accurate information about interface states than ...

In the 1990s, a new type of learning algorithm was developed, based on results from statistical learning theory: the Support Vector Machine (SVM). This gave rise to a new class of theoretically ...

Persistent Link: https://ieeexplore.ieee.org/servlet/opac?punumber=6731005 ...

Abstract: Problems involving the classical linear partial differential equations of mathematical physics can be reduced to algebraic ones of a very much simpler structure by replacing the ...

Internet Of Things,Deep Learning,Unmanned Aerial Vehicles,Deep Reinforcement Learning,Learning Algorithms,Edge Computing,Neural Network,Internet Of Things Devices ...

Book Abstract: This advanced text and reference covers the design and implementation of integrated circuits for analog-to-digital and digital-to-analog conversion. It begins with basic concepts and ...

Abstract: Two machine-learning procedures have been investigated in some detail using the game of checkers. Enough work has been done to verify the fact that a computer can be programmed so that it ...

Abstract: Humans can naturally and effectively find salient regions in complex scenes. Motivated by this observation, attention mechanisms were introduced into computer vision with the aim of ...

Reinforcement learning, one of the most active research areas in artificial intelligence, is a computational approach to learning whereby an agent tries to maximize the total amount of reward it ...