Deep Learning for Cognitive Computing Systems : : Technological Advancements and Applications / / ed. by M.G. Sumithra, Rajesh Kumar Dhanaraj, Celestine Iwendi, Anto Merline Manoharan.
Cognitive computing simulates human thought processes with self-learning algorithms that utilize data mining, pattern recognition, and natural language processing. The integration of deep learning improves the performance of Cognitive computing systems in many applications, helping in utilizing hete...
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Superior document: | Title is part of eBook package: De Gruyter DG Plus DeG Package 2023 Part 1 |
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MitwirkendeR: | |
HerausgeberIn: | |
Place / Publishing House: | Berlin ;, Boston : : De Gruyter, , [2022] ©2023 |
Year of Publication: | 2022 |
Language: | English |
Series: | Smart Computing Applications ,
7 |
Online Access: | |
Physical Description: | 1 online resource (IX, 199 p.) |
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Other title: | Frontmatter -- Contents -- List of Authors -- The Learning of Deep Learning: Overview, Methods, and Applications -- Foundation of Cognitive Computing -- Applications and Implications of Artificial Intelligence and Deep Learning in Computer Vision -- A Study of Voice Recognition System Using Deep Learning Techniques -- Building Machine Learning–Based Prediction System for Critical Diseases -- An Overview of Internet of Things and Machine Learning for Smart Healthcare -- Nutrition Food Recognition Using Deep Learning Algorithm for Physically Challenged Human Being -- Healthcare Data Analysis Using Deep Learning Paradigm -- Cognitive Authentication for Smart Healthcare System -- Cognitive-Inspired Computer Vision Assist System for Diabetic Retinopathy Detection from Fundus Images -- A Novel Deep Belief Neural Network Model for Abstractive Text Summarization -- Index |
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Summary: | Cognitive computing simulates human thought processes with self-learning algorithms that utilize data mining, pattern recognition, and natural language processing. The integration of deep learning improves the performance of Cognitive computing systems in many applications, helping in utilizing heterogeneous data sets and generating meaningful insights. |
Format: | Mode of access: Internet via World Wide Web. |
ISBN: | 9783110750584 9783111175782 9783110993899 9783110994810 9783110994223 9783110994193 |
ISSN: | 2700-6239 ; |
DOI: | 10.1515/9783110750584 |
Access: | restricted access |
Hierarchical level: | Monograph |
Statement of Responsibility: | ed. by M.G. Sumithra, Rajesh Kumar Dhanaraj, Celestine Iwendi, Anto Merline Manoharan. |