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The handbook of research on computer vision and image processing in the deep learning era is designed to serve researchers and developers by sharing original, innovative, and state-of-the-art algorithms and architectures for applications in the areas of computer vision, image processing, biometrics, virtual and augmented reality, and more. It integrates the knowledge of the growing international community of researchers working on the application of machine learning and deep learning methods in vision and robotics. Covering topics such as brain tumor detection, heart disease prediction, and medical image detection, this premier reference source is an exceptional resource for medical professionals, faculty and students of higher education, business leaders and managers, librarians, government officials, researchers, and academicians

Titel:	Handbook of research on computer vision and image processing in the deep learning era
Autor/in / Beteiligte Person:	Srinivasan, A. [Ed.] ; Global, IGI
Link:	http://lobid.org/resources/99208355347106446
Veröffentlichung:	Hershey, Pennsylvania (701 E. Chocolate Avenue, Hershey, Pennsylvania, 17033, USA): IGI Global, 2023
Medientyp:	Buch
Umfang:	31 PDFs (440 pages)
ISBN:	978-1-7998-8894-9 (print) ; 978-1-7998-8892-5 (print) ; 1-7998-8892-4 (print)
DOI:	10.4018/978-1-7998-8892-5
Schlagwort:	Image processing Computer vision
Sonstiges:	Nachgewiesen in: hbz-Verbundkatalog Contents Note: Chapter 1. Acceleration of image processing and computer vision algorithms -- Chapter 2. Acceleration of computer vision and deep learning: surveillance systems -- Chapter 3. Deep learning architecture for a real-time driver safety drowsiness detection system -- Chapter 4. Deep learning-based computer vision for robotics -- Chapter 5. Deep learning for emotion recognition -- Chapter 6. Smart surveillance system using deep learning approaches -- Chapter 7. Role of deep learning in image and video processing -- Chapter 8. Gesture and posture recognition by using deep learning -- Chapter 9. Evolution of deep learning for biometric identification and recognition -- Chapter 10. Hand-crafted feature extraction and deep learning models for leaf image recognition -- Chapter 11. The evolution of image denoising from model-driven to machine learning: a mathematical perspective -- Chapter 12. Machine learning and image processing based computer vision in industry 4.0 -- Chapter 13. Real-time torpidity detection for drivers in machine learning environments -- Chapter 14. Potential market-predictive features based bitcoin price prediction using machine learning algorithms -- Chapter 15. An intelligent 8-queen placement approach of chess game for hiding 56-bit key of DES algorithm over digital color images -- Chapter 16. Deep neural network with feature optimization technique for classification of coronary artery disease -- Chapter 17. Detection and classification of diabetic retinopathy using image processing algorithms, convolutional neural network, and signal processing techniques -- Chapter 18. Image security using visual cryptography -- Chapter 19. Multipath convolutional neural network for brain tumor detection (CNN) -- Chapter 20. Image enhancement under gaussian impulse noise for satellite and medical applications -- Chapter 21. Algorithmic approach for spatial entity and mining -- Chapter 22. A combined feature selection technique for improving classification accuracy -- Chapter 23. Generalization and efficiency on finger print presentation attack anomaly detection -- Chapter 24. Predictive analytics on female infertility using ensemble methods Document Type: Monograph File Description: text

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Handbook of research on computer vision and image processing in the deep learning era