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Visual Attention Mechanism In Deep Learning And Its Applications


Visual Attention Mechanism In Deep Learning And Its Applications
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Visual Attention Mechanism In Deep Learning And Its Applications


Visual Attention Mechanism In Deep Learning And Its Applications
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Author : Shiyang Yan
language : en
Publisher:
Release Date : 2018

Visual Attention Mechanism In Deep Learning And Its Applications written by Shiyang Yan and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018 with categories.




The 13th Conference On Information Technology And Its Applications


The 13th Conference On Information Technology And Its Applications
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Author : Ngoc Thanh Nguyen
language : en
Publisher: Springer Nature
Release Date : 2024-11-07

The 13th Conference On Information Technology And Its Applications written by Ngoc Thanh Nguyen and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-11-07 with Computers categories.


This book presents selected papers from the 13th International Conference on Information Technology and its Applications (CITA 2024) which took place on July 19–20, 2024. The 13th CITA will be hosted by the Vietnam-Korea University of Information and Communication Technology (VKU), a member of University of Danang, with the supports of the researching and training institutions belonging to ASEAN Consortium for Innovation and Research (ACIR) as well as Vietnam ICT Association of Faculties-Institutes-School-Universities (FISU Vietnam). The conference will take place in Da Nang City and Hoi An City which are beautiful and livable cities in Vietnam. All papers submitted to CITA 2024 are reviewed seriously, closely, and thoroughly by 02-04 reviewers with appropriate expertise, with professional advice from reputable scientists in the fields of information and communication technology. Over the past 13 years of establishment and development, CITA has become an international scientific conference with a prestigious brand in the scientific community not only in Vietnam but also around the world in the field of ICT and digital economy. For this edition of the conference, we have received in total 173 papers whose authors come from over 25 countries around the world. Only 43 papers of the highest quality were selected for oral presentation and publication in this LNNS volume. The average rate of papers accepted by this volume is about 25%. Papers included in these proceedings cover the following topics: data science and artificial intelligence, image and natural language processing, software engineering and information system, network and communications, and digital economy. The accepted and presented papers focus on new trends and challenges facing information technology and its applications. The presenters show how research works can stimulate novel and innovative applications. We hope that you find these results useful and inspiring for your future research work.



Visual Attention Mechanisms


Visual Attention Mechanisms
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Author : Virginio Cantoni
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06

Visual Attention Mechanisms written by Virginio Cantoni and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Computers categories.


Proceedings of the Fifth International School on Neural Networks "E.R. Caianiello" on Visual Attention MechaProceedings of the Fifth International School on Neural Networks "E.R. Caianiello" on Visual Attention Mechanisms, held 23-28 October 2000 in Vietri sul Mare, Italy.nisms, held 23-28 October 2000 in Vietri sul Mare, Italy. The book covers a number of broad themes relevant to visual attention, ranging from computer vision to psychology and physiology of vision. The main theme of the book is the attention processes of vision systems and it aims to point out the analogies and the divergences of biological vision with the frameworks introduced by computer scientists in artificial vision.



Deep Learning


Deep Learning
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Author : Manish Soni
language : en
Publisher:
Release Date : 2024-11-13

Deep Learning written by Manish Soni and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-11-13 with Computers categories.


Welcome to "Deep Learning: A Comprehensive Guide," a book meticulously designed to cater to the needs of learners at various stages of their journey into the fascinating world of deep learning. Whether you are a beginner embarking on your first exploration into artificial intelligence or a seasoned professional looking to deepen your expertise, this book aims to be your trusted companion. Deep learning, a subset of machine learning, has revolutionized the field of artificial intelligence, enabling advancements that were once thought to be the stuff of science fiction. From autonomous vehicles to sophisticated natural language processing systems, deep learning has become the backbone of many cutting-edge technologies. Understanding and mastering deep learning is not just a desirable skill but a necessity for anyone looking to thrive in the modern tech landscape. What This Book Offers This book is not just a theoretical exposition but a practical guide designed to provide you with a holistic learning experience. Here's a glimpse of what you can expect: Structured Content: Starts with neural network basics and advances to topics like convolutional, recurrent, and generative adversarial networks. Each chapter builds on the previous, ensuring a comprehensive learning journey. Online Practice Questions: Each chapter includes practice questions from basic to advanced levels to test and reinforce your understanding. Videos: Instructional videos complement the book's content, offering step-by-step explanations and real-life applications. Exercises and Projects: Includes exercises and hands-on projects that simulate real-world problems, providing practical experience. Lab Activities: Features lab activities using frameworks like TensorFlow and PyTorch for hands-on experimentation with deep learning models. Case Studies: Illustrates the application of deep learning in industries such as healthcare, finance, and entertainment, highlighting its transformative potential. Comprehensive Coverage: Covers a broad spectrum of topics, from theoretical foundations to practical implementations, latest advancements, ethical considerations, and future trends. Who Should Use This Book? This book is designed for: Students and Academics: Pursuing studies in computer science, data science, or related fields. Industry Professionals: Enhancing skills or transitioning into roles involving deep learning. Embarking on the journey to master deep learning is both challenging and rewarding. This book is designed to make that journey as smooth and enlightening as possible. We hope that the combination of theoretical knowledge, practical exercises, projects, and real-world applications will equip you with the skills and confidence needed to excel in the field of deep learning.



The Application Of Cnn And Hybrid Networks In Medical Images Processing And Cancer Classification


The Application Of Cnn And Hybrid Networks In Medical Images Processing And Cancer Classification
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Author : Yuriy Zaychenko
language : en
Publisher: Cambridge Scholars Publishing
Release Date : 2023-07-26

The Application Of Cnn And Hybrid Networks In Medical Images Processing And Cancer Classification written by Yuriy Zaychenko and has been published by Cambridge Scholars Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-07-26 with Medical categories.


This book is devoted to the problems of information technologies (IT) and artificial intelligence methods applied to medical image processing, tumour detection and cancer classification in different human organs, including the breasts, lungs and brain. The most efficient modern tools in the problem of medical images processing and analysis are considered- convolutional neural networks (CNN). The main goal of this book is to present and analyze new perspective architectures of CNN aimed to increase accuracy of cancer classification. This book contains new approaches for improving efficiency of cancer detection in comparison with known CNN structures. The numerous experimental investigations proved their better efficiency by different classification criteria as compared with known. This book will be useful to specialists engaged in IT applications in medicine, dealing with development and application of medical diagnostics systems, students and postgraduates in Computer Science, all persons who are interested in IT applications in medicine, medical personnel engaged in malignant tumour diagnostics and cancer detection, and the wider public interested in the problems of cancer diagnostics that desire to extend their knowledge of prospective IT methods and their effectively solutions.



Practical Convolutional Neural Networks


Practical Convolutional Neural Networks
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Author : Mohit Sewak
language : en
Publisher: Packt Publishing Ltd
Release Date : 2018-02-27

Practical Convolutional Neural Networks written by Mohit Sewak and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-02-27 with Computers categories.


One stop guide to implementing award-winning, and cutting-edge CNN architectures Key Features Fast-paced guide with use cases and real-world examples to get well versed with CNN techniques Implement CNN models on image classification, transfer learning, Object Detection, Instance Segmentation, GANs and more Implement powerful use-cases like image captioning, reinforcement learning for hard attention, and recurrent attention models Book Description Convolutional Neural Network (CNN) is revolutionizing several application domains such as visual recognition systems, self-driving cars, medical discoveries, innovative eCommerce and more.You will learn to create innovative solutions around image and video analytics to solve complex machine learning and computer vision related problems and implement real-life CNN models. This book starts with an overview of deep neural networkswith the example of image classification and walks you through building your first CNN for human face detector. We will learn to use concepts like transfer learning with CNN, and Auto-Encoders to build very powerful models, even when not much of supervised training data of labeled images is available. Later we build upon the learning achieved to build advanced vision related algorithms for object detection, instance segmentation, generative adversarial networks, image captioning, attention mechanisms for vision, and recurrent models for vision. By the end of this book, you should be ready to implement advanced, effective and efficient CNN models at your professional project or personal initiatives by working on complex image and video datasets. What you will learn From CNN basic building blocks to advanced concepts understand practical areas they can be applied to Build an image classifier CNN model to understand how different components interact with each other, and then learn how to optimize it Learn different algorithms that can be applied to Object Detection, and Instance Segmentation Learn advanced concepts like attention mechanisms for CNN to improve prediction accuracy Understand transfer learning and implement award-winning CNN architectures like AlexNet, VGG, GoogLeNet, ResNet and more Understand the working of generative adversarial networks and how it can create new, unseen images Who this book is for This book is for data scientists, machine learning and deep learning practitioners, Cognitive and Artificial Intelligence enthusiasts who want to move one step further in building Convolutional Neural Networks. Get hands-on experience with extreme datasets and different CNN architectures to build efficient and smart ConvNet models. Basic knowledge of deep learning concepts and Python programming language is expected.



Bio Inspired Computation And Its Applications


Bio Inspired Computation And Its Applications
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Author : Tinggui Chen
language : en
Publisher: Frontiers Media SA
Release Date : 2023-07-06

Bio Inspired Computation And Its Applications written by Tinggui Chen and has been published by Frontiers Media SA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-07-06 with Science categories.




Intelligent 3d Technologies And Augmented Reality


Intelligent 3d Technologies And Augmented Reality
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Author : Roumen Kountchev (deceased)
language : en
Publisher: Springer Nature
Release Date : 2024-09-02

Intelligent 3d Technologies And Augmented Reality written by Roumen Kountchev (deceased) and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-09-02 with Computers categories.


This book presents high-quality research in the field of 3D imaging technology. The fifth edition of International Conference on 3D Imaging Technology (3DDIT-MSP&DL) continues the good traditions already established by the first four editions of the conference to provide a wide scientific forum for researchers, academia, and practitioners to exchange newest ideas and recent achievements in all aspects of image processing and analysis, together with their contemporary applications. The conference proceedings are published in two volumes. The main topics of the papers comprise famous trends such as: 3D image representation, 3D image technology, 3D images and graphics, and computing and 3D information technology. In these proceedings, special attention is paid at the 3D tensor image representation, the 3D content generation technologies, big data analysis, and also deep learning, artificial intelligence, the 3D image analysis and video understanding, the 3D virtual and augmented reality, and many related areas. The first volume contains papers in 3D image processing, transforms, and technologies. The second volume is about computing and information technologies, computer images, and graphics and related applications. The two volumes of the book cover a wide area of the aspects of the contemporary multidimensional imaging and the related future trends from data acquisition to real-world applications based on various techniques and theoretical approaches.



Deep Learning Applications In Medical Image Segmentation


Deep Learning Applications In Medical Image Segmentation
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Author : Sajid Yousuf Bhat
language : en
Publisher: John Wiley & Sons
Release Date : 2025-01-22

Deep Learning Applications In Medical Image Segmentation written by Sajid Yousuf Bhat 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 2025-01-22 with Computers categories.


Apply revolutionary deep learning technology to the fast-growing field of medical image segmentation Precise medical image segmentation is rapidly becoming one of the most important tools in medical research, diagnosis, and treatment. The potential for deep learning, a technology which is already revolutionizing practice across hundreds of subfields, is immense. The prospect of using deep learning to address the traditional shortcomings of image segmentation demands close inspection and wide proliferation of relevant knowledge. Deep Learning Applications in Medical Image Segmentation meets this demand with a comprehensive introduction and its growing applications. Covering foundational concepts and its advanced techniques, it offers a one-stop resource for researchers and other readers looking for a detailed understanding of the topic. It is deeply engaged with the main challenges and recent advances in the field of deep-learning-based medical image segmentation. Readers will also find: Analysis of deep learning models, including FCN, UNet, SegNet, Dee Lab, and many more Detailed discussion of medical image segmentation divided by area, incorporating all major organs and organ systems Recent deep learning advancements in segmenting brain tumors, retinal vessels, and inner ear structures Analyzes the effectiveness of deep learning models in segmenting lung fields for respiratory disease diagnosis Explores the application and benefits of Generative Adversarial Networks (GANs) in enhancing medical image segmentation Identifies and discusses the key challenges faced in medical image segmentation using deep learning techniques Provides an overview of the latest advancements, applications, and future trends in deep learning for medical image analysis Deep Learning Applications in Medical Image Segmentation is ideal for academics and researchers working with medical image segmentation, as well as professionals in medical imaging, data science, and biomedical engineering.



Advances In Computer Vision From Deep Learning Models To Practical Applications


Advances In Computer Vision From Deep Learning Models To Practical Applications
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Author : Hancheng Zhu
language : en
Publisher: Frontiers Media SA
Release Date : 2025-05-26

Advances In Computer Vision From Deep Learning Models To Practical Applications written by Hancheng Zhu and has been published by Frontiers Media SA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-05-26 with Science categories.


The field of computer vision has experienced remarkable progress in recent years, largely attributed to the unprecedented advancements in deep learning models and their practical applications across diverse domains. This research topic is dedicated to presenting and exploring the latest developments in computer vision, with a particular emphasis on the transition from theoretical deep learning models to their real-world applications. This research topic focuses on the practical application of deep learning models in computer vision, translating theoretical advancements into real-world solutions. It offers a platform to share success stories and case studies illustrating the effective deployment of such models in areas like medical imaging, remote sensing, and multimedia affective computing. Furthermore, with the importance of interpretability and transparency in deep learning models emphasized, these models become more complex and understanding their decision-making processes is crucial.