𝔖 Scriptorium
✦   LIBER   ✦

πŸ“

Multidisciplinary Applications of Deep Learning-Based Artificial Emotional Intelligence

✍ Scribed by Chiranji Lal Chowdhary


Publisher
Engineering Science Reference
Year
2022
Tongue
English
Leaves
324
Series
Advances in Computational Intelligence and Robotics
Category
Library

⬇  Acquire This Volume

No coin nor oath required. For personal study only.

✦ Synopsis


Emotional intelligence has emerged as an important area of research in the artificial intelligence field as it covers a wide range of real-life domains. Though machines may never need all the emotional skills that people need, there is evidence to suggest that machines require at least some of these skills to appear intelligent when interacting with people. To understand how deep learning-based emotional intelligence can be applied and utilized across industries, further study on its opportunities and future directions is required. Multidisciplinary Applications of Deep Learning-Based Artificial Emotional Intelligence explores artificial intelligence applications, such as machine and deep learning, in emotional intelligence and examines their use towards attaining emotional intelligence acceleration and augmentation. It provides research on tools used to simplify and streamline the formation of deep learning for system architects and designers. Covering topics such as data analytics, deep learning, knowledge management, and virtual emotional intelligence, this reference work is ideal for computer scientists, engineers, industry professionals, researchers, scholars, practitioners, academicians, instructors, and students.


πŸ“œ SIMILAR VOLUMES


Risk Modeling: Practical Applications of
✍ Terisa Roberts, Stephen J. Tonna πŸ“‚ Library πŸ“… 2022 πŸ› Wiley 🌐 English

<p><span>A wide-ranging overview of the use ofΒ machine learning and AI techniquesΒ in financial risk management, including practical advice for implementationΒ </span></p><p><span>Risk Modeling:Β Practical Applications of Artificial Intelligence, Machine Learning, and Deep LearningΒ </span><span>introdu

An Intuitive Exploration of Artificial I
✍ Simant Dube πŸ“‚ Library πŸ“… 2021 πŸ› Springer 🌐 English

This book develops a conceptual understanding of Artificial Intelligence (AI), Deep Learning and Machine Learning in the truest sense of the word. It is an earnest endeavor to unravel what is happening at the algorithmic level, to grasp how applications are being built and to show the long adventuro

An Intuitive Exploration of Artificial I
✍ Simant Dube πŸ“‚ Library πŸ“… 2021 πŸ› Springer 🌐 English

<div><div>This book develops a conceptual understanding of Artificial Intelligence (AI), Deep Learning and Machine Learning in the truest sense of the word. It is an earnest endeavor to unravel what is happening at the algorithmic level, to grasp how applications are being built and to show the long

An Intuitive Exploration of Artificial I
✍ Simant Dube πŸ“‚ Library πŸ“… 2021 πŸ› Springer 🌐 English

<span><div><div>This book develops a conceptual understanding of Artificial Intelligence (AI), Deep Learning and Machine Learning in the truest sense of the word. It is an earnest endeavor to unravel what is happening at the algorithmic level, to grasp how applications are being built and to show th

Deep Learning for Power System Applicati
✍ Fangxing Li; Yan Du πŸ“‚ Library πŸ“… 2023 πŸ› Springer International Publishing 🌐 English

This book provides readers with an in-depth review of deep learning-based techniques and discusses how they can benefit power system applications. Representative case studies of deep learning techniques in power systems are investigated and discussed, including convolutional neural networks (CNN) fo

Deep Reinforcement Learning: Frontiers o
✍ Mohit Sewak πŸ“‚ Library πŸ“… 2019 πŸ› Springer 🌐 English

This book starts by presenting the basics of reinforcement learning using highly intuitive and easy-to-understand examples and applications, and then introduces the cutting-edge research advances that make reinforcement learning capable of out-performing most state-of-art systems, and even humans in