Deep learning and parallel computing environment for bioengineering systems. (2019)

• Record Type: Book
• Further Information: Note: Edited by Arun Kumar Sangaiah.
• Editors: Sangaiah, Arun Kumar, 1981-
• Contents: 1. Introductory; 2. Theoretical results on representation of deep learning and parallel architectures for bioengineering; 3. Parallel Machine Learning and Deep Learning approaches for Bio-informatics; 4. Parallel programming, architectures and machine intelligence for bioengineering; 5. Deep Randomized Neural Networks for Bioengineering applications; 6. Artificial Intelligence enhance parallel computing environments; 7. Parallel computing, graphics processing units (GPU) and new hardware for deep learning in Computational Intelligence research; 8. Novel feature representation using deep learning, dictionary learning for face, fingerprint, ocular, and/or other biometric modalities; 9. Novel distance metric learning algorithms for biometrics modalities; 10. Machine learning techniques (e.g., Deep Learning) with cognitive knowledge acquisition frameworks for sustainable energy aware systems; 11. Deep learning and semi-supervised and transfer learning algorithms for medical imaging; 12. Biological plausibility/inspiration of Randomized Neural Networks; 13. Genomic data visualisation and representation for medical information; 14. Applications of deep learning and unsupervised feature learning for prediction of sustainable engineering tasks; 15. Inference and optimization with bioengineering problems
• Publisher Details: Amsterdam : Academic Press
• Publication Date: 2019
• Extent: 1 online resource, illustrations
• Subjects: 660.60285631; Bioengineering -- Data processing; Machine learning; Parallel processing (Electronic computers)
• Languages: English
• ISBNs: 9780128172933
• Related ISBNs: 9780128167182
• Notes: Note: Description based on CIP data; resource not viewed.
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