Deep Learning And Computer Vision Models And Biomedical Applications
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Deep Learning And Computer Vision Models And Biomedical Applications
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Author : Uma N. Dulhare
language : en
Publisher: Springer Nature
Release Date : 2025-03-08
Deep Learning And Computer Vision Models And Biomedical Applications written by Uma N. Dulhare and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-03-08 with Computers categories.
This book takes a balanced approach between theoretical understanding and real time applications. All topics show how to explore, build, evaluate and optimize deep learning models with computer vision. Deep learning is integrated with computer vision to enhance the performance of image classification with localization, object detection, object recognition, object segmentation, image style transfer, image colorization, image reconstruction, image super-resolution, image synthesis, motion detection, pose estimation, semantic segmentation in biomedical field. Huge number of efficient approaches/applications and models support medical decisions in the fields of cardiology, dermatology, and radiology. The content of book elaborates deep learning models such as convolution neural networks, deep learning, generative adversarial network, long short-term memory networks (LSTM), autoencoder (AE), restricted Boltzmann machine (RBM), self-organizing map (SOM), deep belief network (DBN), etc.
Deep Learning And Computer Vision Models And Biomedical Applications
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Author : Uma N. Dulhare
language : en
Publisher: Springer Nature
Release Date : 2025-07-18
Deep Learning And Computer Vision Models And Biomedical Applications written by Uma N. Dulhare and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-07-18 with Computers categories.
This book takes a balanced approach between theoretical understanding and real time applications. All topics show how to explore, build, evaluate and optimize deep learning models with computer vision. Deep learning is integrated with computer vision to enhance the performance of image classification with localization, object detection, object recognition, object segmentation, image style transfer, image colorization, image reconstruction, image super-resolution, image synthesis, motion detection, pose estimation, semantic segmentation in biomedical field. Huge number of efficient approaches/applications and models support medical decisions in the fields of cardiology, dermatology, and radiology. The content of book elaborates deep learning models such as convolution neural networks, deep learning, generative adversarial network, long short-term memory networks (LSTM), autoencoder (AE), restricted Boltzmann machine (RBM), self-organizing map (SOM), deep belief network (DBN), etc.
Machine Learning For Biomedical Applications
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Author : Maria Deprez
language : en
Publisher: Academic Press
Release Date : 2023-09-07
Machine Learning For Biomedical Applications written by Maria Deprez and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-09-07 with Computers categories.
Machine Learning for Biomedical Applications: With Scikit-Learn and PyTorch presents machine learning techniques most commonly used in a biomedical setting. Avoiding a theoretical perspective, it provides a practical and interactive way of learning where concepts are presented in short descriptions followed by simple examples using biomedical data. Interactive Python notebooks are provided with each chapter to complement the text and aid understanding. Sections cover uses in biomedical applications, practical Python coding skills, mathematical tools that underpin the field, core machine learning methods, deep learning concepts with examples in Keras, and much more. This accessible and interactive introduction to machine learning and data analysis skills is suitable for undergraduates and postgraduates in biomedical engineering, computer science, the biomedical sciences and clinicians. - Gives a basic understanding of the most fundamental concepts within machine learning and their role in biomedical data analysis. - Shows how to apply a range of commonly used machine learning and deep learning techniques to biomedical problems. - Develops practical computational skills needed to implement machine learning and deep learning models for biomedical data sets. - Shows how to design machine learning experiments that address specific problems related to biomedical data
Deep Learning For Biomedical Applications
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Author : Utku Kose
language : en
Publisher: CRC Press
Release Date : 2021-07-19
Deep Learning For Biomedical Applications written by Utku Kose and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-07-19 with Technology & Engineering categories.
This book is a detailed reference on biomedical applications using Deep Learning. Because Deep Learning is an important actor shaping the future of Artificial Intelligence, its specific and innovative solutions for both medical and biomedical are very critical. This book provides a recent view of research works on essential, and advanced topics. The book offers detailed information on the application of Deep Learning for solving biomedical problems. It focuses on different types of data (i.e. raw data, signal-time series, medical images) to enable readers to understand the effectiveness and the potential. It includes topics such as disease diagnosis, image processing perspectives, and even genomics. It takes the reader through different sides of Deep Learning oriented solutions. The specific and innovative solutions covered in this book for both medical and biomedical applications are critical to scientists, researchers, practitioners, professionals, and educations who are working in the context of the topics.
Deep And Reinforcement Learning Models And Algorithm
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Author : Dr.R.Jayakarthik
language : en
Publisher: Leilani Katie Publication
Release Date : 2024-04-02
Deep And Reinforcement Learning Models And Algorithm written by Dr.R.Jayakarthik and has been published by Leilani Katie Publication this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-04-02 with Computers categories.
Dr.R.Jayakarthik, Associate Professor and Head, Department of Computational Intelligence, Saveetha College of Liberal Arts and Sciences, Saveetha Institute of Medical and Technical Sciences, Chennai, Tamil Nadu, India. Dr.S.Rukmani Devi, Assistant Professor, Senior Grade, Department of Computer Science, Saveetha College of Liberal Arts and Sciences, Saveetha Institute of Medical and Technical Sciences, Deemed to be University, Chennai, Tamil Nadu, India. Dr.B.Geetha, Associate Professor, Department of Computer Science, Saveetha College of Liberal Arts and Sciences, Saveetha Institute of Medical and Technical Sciences, Chennai, Tamil Nadu, India. Dr.Krishna Priya, Professor, Department of Computer Science, Saveetha College of Liberal Arts and Sciences, Saveetha Institute of Medical and Technical Sciences, Chennai, Tamil Nadu, India.
Machine Learning In Biological Sciences
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Author : Shyamasree Ghosh
language : en
Publisher: Springer Nature
Release Date : 2022-05-04
Machine Learning In Biological Sciences written by Shyamasree Ghosh and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-05-04 with Medical categories.
This book gives an overview of applications of Machine Learning (ML) in diverse fields of biological sciences, including healthcare, animal sciences, agriculture, and plant sciences. Machine learning has major applications in process modelling, computer vision, signal processing, speech recognition, and language understanding and processing and life, and health sciences. It is increasingly used in understanding DNA patterns and in precision medicine. This book is divided into eight major sections, each containing chapters that describe the application of ML in a certain field. The book begins by giving an introduction to ML and the various ML methods. It then covers interesting and timely aspects such as applications in genetics, cell biology, the study of plant-pathogen interactions, and animal behavior. The book discusses computational methods for toxicity prediction of environmental chemicals and drugs, which forms a major domain of research in the field of biology. It is of relevance to post-graduate students and researchers interested in exploring the interdisciplinary areas of use of machine learning and deep learning in life sciences.
Ai Enabled Sustainable Innovations In Education And Business
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Author : Sorayyaei Azar, Ali
language : en
Publisher: IGI Global
Release Date : 2025-04-24
Ai Enabled Sustainable Innovations In Education And Business written by Sorayyaei Azar, Ali and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-04-24 with Computers categories.
Sustainability for the future is an ever-present concern. Modern innovations in education and business are enhancing resources and technology for improved sustainability-driven solutions. Artificial intelligence (AI), specifically, is transforming education and business by providing real-time data processing systems for decision support and streamlining processes. As a result, educators and business leaders are better able to allocate resources and maximize their impact on students, industries, and customers in addition to sustainability. By fostering efficiency and sustainability in education and business, AI may also increase individual environmental awareness and social responsibility. AI-Enabled Sustainable Innovations in Education and Business discusses technological advancements in digital education and learning, and in various industries, including healthcare, finance, and supply chains. It highlights advanced innovations for environmental, economic, and operational sustainability. Covering topics such as information and communication technology (ICT), state government programs, and automated device management, this book is an excellent resource for business leaders, executives, managers, educators, school administrators, technologists, computer engineers, sustainability advocates, professionals, researchers, scholars, academicians, and more.
Hyperspectral Image Analysis
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Author : Saurabh Prasad
language : en
Publisher: Springer Nature
Release Date : 2020-04-27
Hyperspectral Image Analysis written by Saurabh Prasad and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-04-27 with Computers categories.
This book reviews the state of the art in algorithmic approaches addressing the practical challenges that arise with hyperspectral image analysis tasks, with a focus on emerging trends in machine learning and image processing/understanding. It presents advances in deep learning, multiple instance learning, sparse representation based learning, low-dimensional manifold models, anomalous change detection, target recognition, sensor fusion and super-resolution for robust multispectral and hyperspectral image understanding. It presents research from leading international experts who have made foundational contributions in these areas. The book covers a diverse array of applications of multispectral/hyperspectral imagery in the context of these algorithms, including remote sensing, face recognition and biomedicine. This book would be particularly beneficial to graduate students and researchers who are taking advanced courses in (or are working in) the areas of image analysis, machine learning and remote sensing with multi-channel optical imagery. Researchers and professionals in academia and industry working in areas such as electrical engineering, civil and environmental engineering, geosciences and biomedical image processing, who work with multi-channel optical data will find this book useful.
Computer Vision And Image Processing Methods And Applications
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Author : Dr. Parthasarathi De
language : en
Publisher: Chyren Publication
Release Date : 2025-03-12
Computer Vision And Image Processing Methods And Applications written by Dr. Parthasarathi De and has been published by Chyren Publication this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-03-12 with Antiques & Collectibles categories.
Emerging Technologies For Healthcare
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Author : Monika Mangla
language : en
Publisher: John Wiley & Sons
Release Date : 2021-08-17
Emerging Technologies For Healthcare written by Monika Mangla and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-08-17 with Computers categories.
?Emerging Technologies for Healthcare? beginnt mit einer IoT-basierten Lösung für die Automatisierung im Gesundheitssektor, wodurch Verfahren auf Grundlage von fortschrittlichen Deep-Learning-Techniken ermöglicht werden. Praktische Lösungen, die auf verschiedenen Ansätzen des maschinellen Lernens beruhen, werden vorgestellt und auf die Analyse und Vorhersage von Krankheiten angewandt. Ein Beispiel ist die Nutzung einer dreidimensionalen Matrix für die Behandlung chronischer Nierenerkrankungen, die Diagnose und Prognose des erworbenen demyelinisierenden Syndroms und von Autismus-Spektrum-Störungen sowie die Erkennung von Lungenentzündungen. Außerdem werden verschiedene geeignete Ansätze vorgestellt, wie die Gesundheitssysteme mit COVID-19-Fällen umgehen können. Daneben wird ein detaillierter Erkennungsmechanismus dargelegt, mit dessen Hilfe Lösungen entwickelt werden können, um von der Handschrift auf die Persönlichkeit zu schließen, und es werden neuartige Ansätze für die Stimmungsanalyse aufgezeigt, die mit ausreichenden Daten und verschiedenen Betrachtungsweisen untermauert sind. Dieses Buch enthält nicht nur theoretische Ansätze und Algorithmen, sondern zeigt auch auf, welche Schritte bei der Problemanalyse mithilfe von Daten, Prozessen, Berichten und Optimierungstechniken durchlaufen werden. Es ist ein umfassendes Nachschlagewerk für die Lösung verschiedener Probleme anhand von Algorithmen für das maschinelle Lernen.