Healthcare Industry 4.0 (eBook, PDF)
Computer Vision-Aided Data Analytics
Redaktion: Karthikeyan, P.; Rajagopal, R.; Katina, Polinpapilinho F.
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Healthcare Industry 4.0 (eBook, PDF)
Computer Vision-Aided Data Analytics
Redaktion: Karthikeyan, P.; Rajagopal, R.; Katina, Polinpapilinho F.
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This book covers computer vision-based applications in digital health care industry 4.0 including different computer vision techniques, image classification, image segmentations, and object detection
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This book covers computer vision-based applications in digital health care industry 4.0 including different computer vision techniques, image classification, image segmentations, and object detection
Dieser Download kann aus rechtlichen Gründen nur mit Rechnungsadresse in A, B, BG, CY, CZ, D, DK, EW, E, FIN, F, GR, HR, H, IRL, I, LT, L, LR, M, NL, PL, P, R, S, SLO, SK ausgeliefert werden.
Produktdetails
- Produktdetails
- Verlag: Taylor & Francis
- Seitenzahl: 186
- Erscheinungstermin: 28. August 2023
- Englisch
- ISBN-13: 9781000930573
- Artikelnr.: 68402306
- Verlag: Taylor & Francis
- Seitenzahl: 186
- Erscheinungstermin: 28. August 2023
- Englisch
- ISBN-13: 9781000930573
- Artikelnr.: 68402306
- Herstellerkennzeichnung Die Herstellerinformationen sind derzeit nicht verfügbar.
P. Karthikeyan obtained his Bachelor of Engineering (B.E.) in Computer Science and Engineering from Anna University, Chennai, and Tamil Nadu, India, in 2005 and received his Master of Engineering (M.E.) in Computer Science and Engineering from Anna University, Coimbatore, India, in 2009. He completed his Ph.D. degree in ICE from the Anna University, Chennai, in 2018. He is currently completing postdoctoral research at National Chung Cheng University, Taiwan. He is skilled in developing projects and carrying out research in the area of cloud computing and deep learning with programming skills in Java, Python, R and C. He published over 20 articles in international journals with high impact factors and has presented his work at more than 10 international conferences. He has served as a reviewer for prestigious publishers such as Elsevier, Springer, and Inderscience, as well as Scopus indexed journals. Additionally, he currently serves as an editorial board member for several journals, including the EAI Endorsed Transactions on Energy Web, The International Arab Journal of Information Technology and Blue Eyes Intelligence Engineering and Sciences Publication Journal. Polinpapilinho F. Katina is an Assistant Professor in the Department of Informatics and Engineering Systems at the University of South Carolina Upstate, Spartanburg, South Carolina, USA. He previously served as a Postdoctoral Researcher for the National Centers for System of Systems Engineering in Norfolk, Virginia, USA, and Adjunct Professor in the Department of Engineering Management and Systems Engineering at Old Dominion University, Norfolk, Virginia, USA. Dr. Katina holds a B.Sc. in Engineering Technology with a minor in Engineering Management, a M. Eng. in Systems Engineering, and a Ph.D. in Engineering Management/Systems Engineering, all from Old Dominion University. He has received additional training from, among others, the Environmental Systems Research Institute in Redlands, California, USA, and Politecnico di Milano in Milan, Italy. His areas of research/teaching include, among others, complex system governance, critical infrastructure systems, decision-making and analysis (under uncertainty), emerging technologies, energy systems (smart grids), engineering management, infranomics, manufacturing systems, system of systems, systems engineering, systems pathology, and systems thinking. R. Rajagopal received his Bachelor of Engineering (B.E.) in Computer Science and Engineering from Anna University, Chennai, and Tamil Nadu, India, in 2005, his Master of Engineering (M.E.) in Computer Science and Engineering from Anna University, Coimbatore, India, in 2009, and his Ph.D. degree in Anna University, Chennai, in 2018. He has served as a reviewer for reputed Scopus indexed journals and Inderscience. He is also an editorial board member of several journals, including the International Journal of Mathematical Science, Engineering, and Sciences Publication. His research work has been published in over 22 international journals, and he has presented at more than 20 international conferences.
1. Introduction to Computer Vision Aided Data Analytics in Healthcare
Industry 4.0 2. Deep Learning Techniques for Foetal and Infant Data
Processing in a Medical Context 3. Analysis of Detecting Brain Tumors Using
Deep Learning Algorithms 4. Secured Data Dissemination in a Real-Time
Health Care System 5. Modality Classification of Human Emotion 6. COVID-19
Alert Zone Detection Using OpenCV 7. Feature Fusion Model for Heart Disease
Diagnosis 8. Deep Learning and Its Applications in Health Care 9. Future of
Computer Vision Application in Digital Healthcare 10. Study of Computer
Vision Applications in Healthcare Industry 4.0
Industry 4.0 2. Deep Learning Techniques for Foetal and Infant Data
Processing in a Medical Context 3. Analysis of Detecting Brain Tumors Using
Deep Learning Algorithms 4. Secured Data Dissemination in a Real-Time
Health Care System 5. Modality Classification of Human Emotion 6. COVID-19
Alert Zone Detection Using OpenCV 7. Feature Fusion Model for Heart Disease
Diagnosis 8. Deep Learning and Its Applications in Health Care 9. Future of
Computer Vision Application in Digital Healthcare 10. Study of Computer
Vision Applications in Healthcare Industry 4.0
1. Introduction to Computer Vision Aided Data Analytics in Healthcare
Industry 4.0 2. Deep Learning Techniques for Foetal and Infant Data
Processing in a Medical Context 3. Analysis of Detecting Brain Tumors Using
Deep Learning Algorithms 4. Secured Data Dissemination in a Real-Time
Health Care System 5. Modality Classification of Human Emotion 6. COVID-19
Alert Zone Detection Using OpenCV 7. Feature Fusion Model for Heart Disease
Diagnosis 8. Deep Learning and Its Applications in Health Care 9. Future of
Computer Vision Application in Digital Healthcare 10. Study of Computer
Vision Applications in Healthcare Industry 4.0
Industry 4.0 2. Deep Learning Techniques for Foetal and Infant Data
Processing in a Medical Context 3. Analysis of Detecting Brain Tumors Using
Deep Learning Algorithms 4. Secured Data Dissemination in a Real-Time
Health Care System 5. Modality Classification of Human Emotion 6. COVID-19
Alert Zone Detection Using OpenCV 7. Feature Fusion Model for Heart Disease
Diagnosis 8. Deep Learning and Its Applications in Health Care 9. Future of
Computer Vision Application in Digital Healthcare 10. Study of Computer
Vision Applications in Healthcare Industry 4.0