| Description |
1 online resource (x, 209 pages : illustrations (chiefly color)) |
| Series |
EAI/Springer innovations in communication and computing |
|
EAI/Springer innovations in communication and computing.
|
| Contents |
Part I. Concepts of Deep Learning: Recognition Systems -- Emotion Recognition from Speech Using Deep Neural Network -- Text-Independent Speaker Recognition Using Deep Learning -- A Qualitative and Quantitative Research of Machine Learning Algorithms for Gait Analysis and Recognition -- Emotion Recognition from Speech Signals Using Machine Learning and Deep Learning Techniques -- Micro-expression Detection Using Main Directional Maximal Differential Analysis (MDMD) Method -- Part II. Concepts of Deep Learning: Healthcare Systems -- Survival Prediction of Cancer Patient Using Machine Learning -- Skin Lesion Segmentation Using Deep Convolutional Networks -- Bone Cancer Survivability Prognosis with KNN and Genetic Algorithms -- BeamAtt: Generating Medical Diagnosis from Chest X-Rays Using Sampling-Based Intelligence -- Part III. Real-Time Applications of Deep Learning -- CNN-Based Driver Drowsiness Detection System -- Forecasting Using Deep Learning Approaches -- A Low-Cost IOT and Deep Learning Enabled Precision Agriculture Support System for Indian Diverse Environment |
| Summary |
This book provides readers with a comprehensive and recent exposition in deep learning and its multidisciplinary applications, with a concentration on advances of deep learning architectures. The book discusses various artificial intelligence (AI) techniques based on deep learning architecture with applications in natural language processing, semantic knowledge, forecasting and many more. The authors shed light on various applications that can benefit from the use of deep learning in pattern recognition, person re-identification in surveillance videos, action recognition in videos, image and video captioning. The book also highlights how deep learning concepts can be interwoven with more modern concepts to yield applications in multidisciplinary fields. Presents a comprehensive look at deep learning and its multidisciplinary applications, concentrating on advances of deep learning architectures; Includes a survey of deep learning problems and solutions, identifying the main open issues, innovations and latest technologies; Shows industrial deep learning in practice with examples/cases, efforts, challenges, and strategic approaches |
| Notes |
Includes index |
|
Online resource; title from PDF title page (SpringerLink, viewed October 7, 2021) |
| Subject |
Machine learning.
|
|
Machine learning
|
| Form |
Electronic book
|
| Author |
Srivastava, Smriti, editor.
|
|
Khari, Manju, editor.
|
|
Gonzalez Crespo, Ruben, editor
|
|
Chaudhary, Gopal, editor.
|
|
Arora, Parul, editor
|
| ISBN |
9783030761677 |
|
3030761673 |
|
