Skip to content 
el cat en
База данных: ELS EBSCO eBook
Page 1, Results: 5
Отмеченные записи: 0
1.
Подробнее
D 30
Deep learning applications in medical imaging / / [edited by] Sanjay Saxena, Sudip Paul. - 4018/978-1-7998-5071-7. - Hershey, PA : : IGI Global, Medical Information Science Reference,, [2021]. - 1 online resource : : il ( час. мин.), 4018/978-1-7998-5071-7. - (Advances in medical technologies and clinical practice (AMTCP) book series). - Includes bibliographical references and index. - URL: https://library.dvfu.ru/lib/document/SK_ELIB/0C4AA233-F5C0-481B-BFC4-9D4470DBE825. - ISBN 1799850722 (electronic book). - ISBN 9781799850724 (electronic bk.)
"Premier Reference Source" -- Cover. Description based on online resource; title from digital title page (viewed on February 24, 2021).
Параллельные издания: Print version: : Deep learning applications in medical imaging. - Hershey, PA : Medical Information Science Reference, [2021]. - ISBN 9781799850717
Содержание:
Relevance of Machine Learning to Cardiovascular Imaging / Sumesh Sasidharan, Mohammad Salmasi, Selene Pirola, Omar Jarral -- Deep Learning Applications in Medical Imaging : Artificial Intelligence, Machine Learning and Deep Learning / S. Sasikala, S.J. Subhashini, P. Alli, J. Jane Rubel Angelina -- A Survey on Prematurity Detection of Diabetic Retinopathy Based on Fundus Images using Deep Learning Techniques / Amiya Dash, Puspanjali Mohapatra -- Malaria Parasites Detection Using Deep Neural Network / Biswajit Jena, Pulkit Thakar, Vedanta Nayak, Gopal Nayak, Sanjay Saxena -- Deep Learning for Medical Image Segmentation / Kanchan Sarkar, Bohang Li -- Current Trends in Integrating the Concept of Deep Learning in Medical Imaging / Kavitha S. Velammal, Anchitaalagammai J.V., S Murali, Grace Shalini T. -- A CONVblock For Convolutional Neural Networks / Hmidi Alaeddine, Malek Jihene -- Machine Learning for Prediction of Lung Cancer / Nikita Banerjee, Subhalaxmi Das -- Conventional and Non Conventional ANN's in Medical Diagnostics A Tutorial Survey of Architectures, Algorithms and Application / Devika G., Asha Karegowda.
~РУБ DDC 616.07/54
Рубрики: Diagnostic imaging.
Machine learning.
Diagnostic Imaging.
Deep Learning.
Medical Informatics Applications.
Image Processing, Computer-Assisted.
Diagnostic imaging--Digital techniques
Machine learning
Medical informatics
Аннотация: "This book explores the application deep learning in medical imaging"--
Доп.точки доступа:
Saxena, Sanjay, (1986-) \editor.\
Paul, Sudip, (1984-) \editor.\
D 30
Deep learning applications in medical imaging / / [edited by] Sanjay Saxena, Sudip Paul. - 4018/978-1-7998-5071-7. - Hershey, PA : : IGI Global, Medical Information Science Reference,, [2021]. - 1 online resource : : il ( час. мин.), 4018/978-1-7998-5071-7. - (Advances in medical technologies and clinical practice (AMTCP) book series). - Includes bibliographical references and index. - URL: https://library.dvfu.ru/lib/document/SK_ELIB/0C4AA233-F5C0-481B-BFC4-9D4470DBE825. - ISBN 1799850722 (electronic book). - ISBN 9781799850724 (electronic bk.)
"Premier Reference Source" -- Cover. Description based on online resource; title from digital title page (viewed on February 24, 2021).
Параллельные издания: Print version: : Deep learning applications in medical imaging. - Hershey, PA : Medical Information Science Reference, [2021]. - ISBN 9781799850717
Содержание:
Relevance of Machine Learning to Cardiovascular Imaging / Sumesh Sasidharan, Mohammad Salmasi, Selene Pirola, Omar Jarral -- Deep Learning Applications in Medical Imaging : Artificial Intelligence, Machine Learning and Deep Learning / S. Sasikala, S.J. Subhashini, P. Alli, J. Jane Rubel Angelina -- A Survey on Prematurity Detection of Diabetic Retinopathy Based on Fundus Images using Deep Learning Techniques / Amiya Dash, Puspanjali Mohapatra -- Malaria Parasites Detection Using Deep Neural Network / Biswajit Jena, Pulkit Thakar, Vedanta Nayak, Gopal Nayak, Sanjay Saxena -- Deep Learning for Medical Image Segmentation / Kanchan Sarkar, Bohang Li -- Current Trends in Integrating the Concept of Deep Learning in Medical Imaging / Kavitha S. Velammal, Anchitaalagammai J.V., S Murali, Grace Shalini T. -- A CONVblock For Convolutional Neural Networks / Hmidi Alaeddine, Malek Jihene -- Machine Learning for Prediction of Lung Cancer / Nikita Banerjee, Subhalaxmi Das -- Conventional and Non Conventional ANN's in Medical Diagnostics A Tutorial Survey of Architectures, Algorithms and Application / Devika G., Asha Karegowda.
Рубрики: Diagnostic imaging.
Machine learning.
Diagnostic Imaging.
Deep Learning.
Medical Informatics Applications.
Image Processing, Computer-Assisted.
Diagnostic imaging--Digital techniques
Machine learning
Medical informatics
Аннотация: "This book explores the application deep learning in medical imaging"--
Доп.точки доступа:
Saxena, Sanjay, (1986-) \editor.\
Paul, Sudip, (1984-) \editor.\
2.
Подробнее
A 28
AI innovation in medical imaging diagnostics / / Kalaivani Anbarasan, editor. - Hershey, PA : : Medical Information Science Reference,, [2020]. - 1 online resource. - Includes bibliographical references and index. - URL: https://library.dvfu.ru/lib/document/SK_ELIB/05B9794F-19B2-4EA7-B91F-B6E902D72FC7. - ISBN 1799830934. - ISBN 9781799830931 (electronic bk.)
Print version record and CIP data provided by publisher; resource not viewed.
Параллельные издания: Print version: : AI innovation in medical imaging diagnostics. - Hershey, PA : Medical Information Science Reference, [2020]. - ISBN 9781799830924
Содержание:
Ant colony optimization (ACO) based improved edge detection algorithm for segmentation of brain tumor / Devi Thiyagarajan, Deepa Narayanan -- Intelligent mental health analyzer by biofeedback : app and analysis / Rohit Rastogi, Devendra Chaturvedi, Mayank Gupta -- Deep learning based assistive healthcare application for cervical cytology diagnosis and prognosis / Elakkiya, R. -- Detection of tumor from brain MRI images using supervised and unsupervised methods / Kannan, S., Anusuya, S. -- Deep learning based Parkinson's disease prediction system / Padmapriya, G., Elakkiya, R., Aruna, M., Arthi, B. -- A novel method to diagnos the epileptic seizure using machine learning algorithms and scalp EEG signals / Rashmita Khilar -- An automated computer diagnosis system for women breast cancer using deep learning / Kalaivani Anbarasan, Charlyn Puspalatha -- Artificial intelligence perspective on precision medicine / Rehab A. Rayan -- Intracranial hemorrahage detection using convolutional neural network / M. Raja Suguna -- Machine learning algorithm for medical image analysis / M. Vinoth Kumar, G. Padmapriya -- Machine learning in health care / Debasree Mitra, Apurba Paul, Sumanta Chatterjee.
~РУБ DDC 616.07/54
Рубрики: Artificial Intelligence.
Diagnostic Imaging--methods.
Deep Learning.
Machine Learning.
Artificial intelligence.
Diagnostic imaging.
Аннотация: "This book examines the application of artificial intelligence in medical imaging diagnostics"--
Доп.точки доступа:
Anbarasan, Kalaivani, (1975-) \editor.\
A 28
AI innovation in medical imaging diagnostics / / Kalaivani Anbarasan, editor. - Hershey, PA : : Medical Information Science Reference,, [2020]. - 1 online resource. - Includes bibliographical references and index. - URL: https://library.dvfu.ru/lib/document/SK_ELIB/05B9794F-19B2-4EA7-B91F-B6E902D72FC7. - ISBN 1799830934. - ISBN 9781799830931 (electronic bk.)
Print version record and CIP data provided by publisher; resource not viewed.
Параллельные издания: Print version: : AI innovation in medical imaging diagnostics. - Hershey, PA : Medical Information Science Reference, [2020]. - ISBN 9781799830924
Содержание:
Ant colony optimization (ACO) based improved edge detection algorithm for segmentation of brain tumor / Devi Thiyagarajan, Deepa Narayanan -- Intelligent mental health analyzer by biofeedback : app and analysis / Rohit Rastogi, Devendra Chaturvedi, Mayank Gupta -- Deep learning based assistive healthcare application for cervical cytology diagnosis and prognosis / Elakkiya, R. -- Detection of tumor from brain MRI images using supervised and unsupervised methods / Kannan, S., Anusuya, S. -- Deep learning based Parkinson's disease prediction system / Padmapriya, G., Elakkiya, R., Aruna, M., Arthi, B. -- A novel method to diagnos the epileptic seizure using machine learning algorithms and scalp EEG signals / Rashmita Khilar -- An automated computer diagnosis system for women breast cancer using deep learning / Kalaivani Anbarasan, Charlyn Puspalatha -- Artificial intelligence perspective on precision medicine / Rehab A. Rayan -- Intracranial hemorrahage detection using convolutional neural network / M. Raja Suguna -- Machine learning algorithm for medical image analysis / M. Vinoth Kumar, G. Padmapriya -- Machine learning in health care / Debasree Mitra, Apurba Paul, Sumanta Chatterjee.
Рубрики: Artificial Intelligence.
Diagnostic Imaging--methods.
Deep Learning.
Machine Learning.
Artificial intelligence.
Diagnostic imaging.
Аннотация: "This book examines the application of artificial intelligence in medical imaging diagnostics"--
Доп.точки доступа:
Anbarasan, Kalaivani, (1975-) \editor.\
3.
Подробнее
A 67
Applications of machine learning and deep learning for privacy and cybersecurity / / Victor Lobo, Anacleto Correia. - Hershey, PA : : Information Science Reference, an imprint of IGI Global,, [2022]. - 1 online resource (xxi, 271 pages) : : il. - (Advances in information security, privacy, and ethics (AISPE) book series). - Includes bibliographical references and index. - URL: https://library.dvfu.ru/lib/document/SK_ELIB/620C266F-6112-440F-98AD-81BAE40F2B70. - ISBN 9781799894322 (electronic book). - ISBN 1799894320 (electronic book). - ISBN 9781799894339 (electronic bk.). - ISBN 1799894339 (electronic bk.)
Description based on online resource; title from digital title page (viewed on October 04, 2022).
Параллельные издания: Print version: : Applications of machine learning and deep learning for privacy and cybersecurity. - Hershey, PA : Information Science Reference, an imprint of IGI Global, [2022]. - ISBN 9781799894308
Содержание:
Chapter 1. User profiling using keystroke dynamics and rotation forest -- Chapter 2. Predictive modelling for financial fraud detection using data analytics: a gradient-boosting decision tree -- Chapter 3. Comprehensive overview of autonomous vehicles and their security against DDoS attacks -- Chapter 4. Application of machine learning to user behavior-based authentication in smartphone and web -- Chapter 5. The role of deception in securing our cyberspace: honeypots are a viable option -- Chapter 6. Holistic view on detecting DDoS attacks using machine learning -- Chapter 7. Masked transient effect ring oscillator physical unclonable function against machine learning attacks -- Chapter 8. Detecting bank financial fraud in South Africa using a logistic model tree -- Chapter 9. Innovative legitimate non-traditional doctorate programs in cybersecurity, engineering, and technology -- Chapter 10. Privacy preservation of image data with machine learning.
~РУБ DDC 005.8
Рубрики: Computer networks--Security measures--Data processing.
Computer security.
Deep learning (Machine learning)
Computer security.
Deep learning (Machine learning)
Аннотация: "This comprehensive and timely book provides an overview of the field of Machine and Deep Learning in the areas of cybersecurity and privacy, followed by an in-depth view of emerging research exploring the theoretical aspects of machine and deep learning, as well as real-world implementations"--
Доп.точки доступа:
Lobo, Victor, (1965-) \editor.\
Correia, Anacleto, (1961-) \editor.\
A 67
Applications of machine learning and deep learning for privacy and cybersecurity / / Victor Lobo, Anacleto Correia. - Hershey, PA : : Information Science Reference, an imprint of IGI Global,, [2022]. - 1 online resource (xxi, 271 pages) : : il. - (Advances in information security, privacy, and ethics (AISPE) book series). - Includes bibliographical references and index. - URL: https://library.dvfu.ru/lib/document/SK_ELIB/620C266F-6112-440F-98AD-81BAE40F2B70. - ISBN 9781799894322 (electronic book). - ISBN 1799894320 (electronic book). - ISBN 9781799894339 (electronic bk.). - ISBN 1799894339 (electronic bk.)
Description based on online resource; title from digital title page (viewed on October 04, 2022).
Параллельные издания: Print version: : Applications of machine learning and deep learning for privacy and cybersecurity. - Hershey, PA : Information Science Reference, an imprint of IGI Global, [2022]. - ISBN 9781799894308
Содержание:
Chapter 1. User profiling using keystroke dynamics and rotation forest -- Chapter 2. Predictive modelling for financial fraud detection using data analytics: a gradient-boosting decision tree -- Chapter 3. Comprehensive overview of autonomous vehicles and their security against DDoS attacks -- Chapter 4. Application of machine learning to user behavior-based authentication in smartphone and web -- Chapter 5. The role of deception in securing our cyberspace: honeypots are a viable option -- Chapter 6. Holistic view on detecting DDoS attacks using machine learning -- Chapter 7. Masked transient effect ring oscillator physical unclonable function against machine learning attacks -- Chapter 8. Detecting bank financial fraud in South Africa using a logistic model tree -- Chapter 9. Innovative legitimate non-traditional doctorate programs in cybersecurity, engineering, and technology -- Chapter 10. Privacy preservation of image data with machine learning.
Рубрики: Computer networks--Security measures--Data processing.
Computer security.
Deep learning (Machine learning)
Computer security.
Deep learning (Machine learning)
Аннотация: "This comprehensive and timely book provides an overview of the field of Machine and Deep Learning in the areas of cybersecurity and privacy, followed by an in-depth view of emerging research exploring the theoretical aspects of machine and deep learning, as well as real-world implementations"--
Доп.точки доступа:
Lobo, Victor, (1965-) \editor.\
Correia, Anacleto, (1961-) \editor.\
4.
Подробнее
D 30
Deep Learning : : Research and Applications / / edited by Siddhartha Bhattacharyya, Vaclav Snasel, Aboul Ella Hassanien, Satadal Saha, B. K. Tripathy. - 1515/9783110670905. - Berlin ; ; Boston : : De Gruyter,, ©2020. - 1 online resource (IX, 152 p.). ( час. мин.), 1515/9783110670905. - (De Gruyter Frontiers in Computational Intelligence ; ; volume 7). - In English. - Includes bibliographical references and index. - URL: https://library.dvfu.ru/lib/document/SK_ELIB/A6744D2D-9D62-4B48-93ED-B318614EC4E0. - ISBN 9783110670929 (electronic bk.). - ISBN 3110670925 (electronic bk.). - ISBN 9783110670905 (electronic book). - ISBN 3110670909 (electronic book)
Description based on online resource; title from PDF title page (publisher's Web site, viewed 23. Jun 2020).
Параллельные издания:
1.
2.
~РУБ DDC 006.3/1
Рубрики: Machine learning.
Artificial intelligence--Industrial applications.
Algorithmus.
Deep Learning.
Maschinelles Lernen.
Neuronales Netz.
COMPUTERS / Intelligence (AI) & Semantics.
Artificial intelligence--Industrial applications
Machine learning
Аннотация: This book focuses on the fundamentals of deep learning along with reporting on the current state-of-art research on deep learning. In addition, it provides an insight of deep neural networks in action with illustrative coding examples. Deep learning is a new area of machine learning research which has been introduced with the objective of moving ML closer to one of its original goals, i.e. artificial intelligence. Deep learning was developed as an ML approach to deal with complex input-output mappings. While traditional methods successfully solve problems where final value is a simple function of input data, deep learning techniques are able to capture composite relations between non-immediately related fields, for example between air pressure recordings and English words, millions of pixels and textual description, brand-related news and future stock prices and almost all real world problems. Deep learning is a class of nature inspired machine learning algorithms that uses a cascade of multiple layers of nonlinear processing units for feature extraction and transformation. Each successive layer uses the output from the previous layer as input. The learning may be supervised (e.g. classification) and/or unsupervised (e.g. pattern analysis) manners. These algorithms learn multiple levels of representations that correspond to different levels of abstraction by resorting to some form of gradient descent for training via backpropagation. Layers that have been used in deep learning include hidden layers of an artificial neural network and sets of propositional formulas. They may also include latent variables organized layer-wise in deep generative models such as the nodes in deep belief networks and deep boltzmann machines. Deep learning is part of state-of-the-art systems in various disciplines, particularly computer vision, automatic speech recognition (ASR) and human action recognition.
Доп.точки доступа:
Bhattacharyya, Siddhartha, \ed.\
Ella Hassanien, Aboul, \ed.\
Saha, Satadal, \ed.\
Snasel, Vaclav, \ed.\
Tripathy, B. K., \ed.\
D 30
Deep Learning : : Research and Applications / / edited by Siddhartha Bhattacharyya, Vaclav Snasel, Aboul Ella Hassanien, Satadal Saha, B. K. Tripathy. - 1515/9783110670905. - Berlin ; ; Boston : : De Gruyter,, ©2020. - 1 online resource (IX, 152 p.). ( час. мин.), 1515/9783110670905. - (De Gruyter Frontiers in Computational Intelligence ; ; volume 7). - In English. - Includes bibliographical references and index. - URL: https://library.dvfu.ru/lib/document/SK_ELIB/A6744D2D-9D62-4B48-93ED-B318614EC4E0. - ISBN 9783110670929 (electronic bk.). - ISBN 3110670925 (electronic bk.). - ISBN 9783110670905 (electronic book). - ISBN 3110670909 (electronic book)
Description based on online resource; title from PDF title page (publisher's Web site, viewed 23. Jun 2020).
Параллельные издания:
1.
2.
Рубрики: Machine learning.
Artificial intelligence--Industrial applications.
Algorithmus.
Deep Learning.
Maschinelles Lernen.
Neuronales Netz.
COMPUTERS / Intelligence (AI) & Semantics.
Artificial intelligence--Industrial applications
Machine learning
Аннотация: This book focuses on the fundamentals of deep learning along with reporting on the current state-of-art research on deep learning. In addition, it provides an insight of deep neural networks in action with illustrative coding examples. Deep learning is a new area of machine learning research which has been introduced with the objective of moving ML closer to one of its original goals, i.e. artificial intelligence. Deep learning was developed as an ML approach to deal with complex input-output mappings. While traditional methods successfully solve problems where final value is a simple function of input data, deep learning techniques are able to capture composite relations between non-immediately related fields, for example between air pressure recordings and English words, millions of pixels and textual description, brand-related news and future stock prices and almost all real world problems. Deep learning is a class of nature inspired machine learning algorithms that uses a cascade of multiple layers of nonlinear processing units for feature extraction and transformation. Each successive layer uses the output from the previous layer as input. The learning may be supervised (e.g. classification) and/or unsupervised (e.g. pattern analysis) manners. These algorithms learn multiple levels of representations that correspond to different levels of abstraction by resorting to some form of gradient descent for training via backpropagation. Layers that have been used in deep learning include hidden layers of an artificial neural network and sets of propositional formulas. They may also include latent variables organized layer-wise in deep generative models such as the nodes in deep belief networks and deep boltzmann machines. Deep learning is part of state-of-the-art systems in various disciplines, particularly computer vision, automatic speech recognition (ASR) and human action recognition.
Доп.точки доступа:
Bhattacharyya, Siddhartha, \ed.\
Ella Hassanien, Aboul, \ed.\
Saha, Satadal, \ed.\
Snasel, Vaclav, \ed.\
Tripathy, B. K., \ed.\
5.
Подробнее
D 30
Deep neural networks for multimodal imaging and biomedical applications / / Annamalai Suresh, R. Udendran, S. Vimal. - 4018/978-1-7998-3591-2. - Hershey, PA : : Medical Information Science Reference, an imprint of IGI Global,, [2020]. - 1 online resource (xvi, 294 pages) : : il ( час. мин.), 4018/978-1-7998-3591-2. - (Advances in bioinformatics and biomedical engineering (ABBE) book series). - Includes bibliographical references and index. - URL: https://library.dvfu.ru/lib/document/SK_ELIB/36D920A4-1DD0-4BE6-889A-FE7B2FAC7F16. - ISBN 9781799835929 (electronic book). - ISBN 1799835928 (electronic book). - ISBN 1799835936. - ISBN 9781799835936 (electronic bk.)
"Premier Reference Source" -- taken from front cover. Description based on online resource; title from digital title page (viewed on August 06, 2020).
Параллельные издания: Print version: : Deep neural networks for multimodal imaging and biomedical applications. - Hershey, PA : Medical Information Science Reference, [2020]. - ISBN 9781799835912
Содержание:
The Pivotal Role of Edge Computing With Machine Learning And It's Impact On Healthcare / Muthukumari S.M., George Dharma Prakash Raj -- Exploring Internet of Things and Artificial Intelligence for smart Healthcare solutions / G. Yamini Yamini -- A Comparative Study of Popular CNN Topologies Used For Imagenet Classification / Hmidi Alaeddine, Malek Jihene -- Advancements in Techniques of Biomedical Image Analysis / Rajitha B. -- Demystification of Deep Learning-driven Medical Image Processing and its impact on future Biomedical Applications / Udendhran Mudaliyar, M. Bala Murugan, Suresh Annamalai -- Transforming Biomedical Applications through Smart Sensing and Artificial Intelligence / Harini T.J., Suresh V., Carmel M. -- Use of eggshell as partial replacement for sand in concrete used in biomedical applications / Sebastin S., Murali Ram Kumar S.M. -- Deep Learning Models for Semantic Multi modal Medical Image Segmentation / V.R.S. Mani.
~РУБ DDC 610.285
Рубрики: Machine learning.
Computational intelligence.
Artificial intelligence--Medical applications.
Deep Learning
Multimodal Imaging--methods
Image Interpretation, Computer-Assisted--methods
Biomedical Technology--methods
Apprentissage automatique.
Intelligence informatique.
Intelligence artificielle en médecine.
Apprentissage profond.
Artificial intelligence--Medical applications
Computational intelligence
Machine learning
Аннотация: "This book provides research exploring the theoretical and practical aspects of emerging data computing methods and imaging techniques within healthcare and biomedicine. The publication provides a complete set of information in a single module starting from developing deep neural networks to predicting disease by employing multi-modal imaging"--
Доп.точки доступа:
Suresh, Annamalai, (1977-) \editor.\
Udendran, R., (1992-) \editor.\
Vimal, S., (1984-) \editor.\
D 30
Deep neural networks for multimodal imaging and biomedical applications / / Annamalai Suresh, R. Udendran, S. Vimal. - 4018/978-1-7998-3591-2. - Hershey, PA : : Medical Information Science Reference, an imprint of IGI Global,, [2020]. - 1 online resource (xvi, 294 pages) : : il ( час. мин.), 4018/978-1-7998-3591-2. - (Advances in bioinformatics and biomedical engineering (ABBE) book series). - Includes bibliographical references and index. - URL: https://library.dvfu.ru/lib/document/SK_ELIB/36D920A4-1DD0-4BE6-889A-FE7B2FAC7F16. - ISBN 9781799835929 (electronic book). - ISBN 1799835928 (electronic book). - ISBN 1799835936. - ISBN 9781799835936 (electronic bk.)
"Premier Reference Source" -- taken from front cover. Description based on online resource; title from digital title page (viewed on August 06, 2020).
Параллельные издания: Print version: : Deep neural networks for multimodal imaging and biomedical applications. - Hershey, PA : Medical Information Science Reference, [2020]. - ISBN 9781799835912
Содержание:
The Pivotal Role of Edge Computing With Machine Learning And It's Impact On Healthcare / Muthukumari S.M., George Dharma Prakash Raj -- Exploring Internet of Things and Artificial Intelligence for smart Healthcare solutions / G. Yamini Yamini -- A Comparative Study of Popular CNN Topologies Used For Imagenet Classification / Hmidi Alaeddine, Malek Jihene -- Advancements in Techniques of Biomedical Image Analysis / Rajitha B. -- Demystification of Deep Learning-driven Medical Image Processing and its impact on future Biomedical Applications / Udendhran Mudaliyar, M. Bala Murugan, Suresh Annamalai -- Transforming Biomedical Applications through Smart Sensing and Artificial Intelligence / Harini T.J., Suresh V., Carmel M. -- Use of eggshell as partial replacement for sand in concrete used in biomedical applications / Sebastin S., Murali Ram Kumar S.M. -- Deep Learning Models for Semantic Multi modal Medical Image Segmentation / V.R.S. Mani.
Рубрики: Machine learning.
Computational intelligence.
Artificial intelligence--Medical applications.
Deep Learning
Multimodal Imaging--methods
Image Interpretation, Computer-Assisted--methods
Biomedical Technology--methods
Apprentissage automatique.
Intelligence informatique.
Intelligence artificielle en médecine.
Apprentissage profond.
Artificial intelligence--Medical applications
Computational intelligence
Machine learning
Аннотация: "This book provides research exploring the theoretical and practical aspects of emerging data computing methods and imaging techniques within healthcare and biomedicine. The publication provides a complete set of information in a single module starting from developing deep neural networks to predicting disease by employing multi-modal imaging"--
Доп.точки доступа:
Suresh, Annamalai, (1977-) \editor.\
Udendran, R., (1992-) \editor.\
Vimal, S., (1984-) \editor.\
Page 1, Results: 5